@article {14430,
	title = {Dynamic Processing Allocation in Video},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {33},
	year = {2011},
	month = {2011/11//},
	pages = {2174 - 2187},
	abstract = {Large stores of digital video pose severe computational challenges to existing video analysis algorithms. In applying these algorithms, users must often trade off processing speed for accuracy, as many sophisticated and effective algorithms require large computational resources that make it impractical to apply them throughout long videos. One can save considerable effort by applying these expensive algorithms sparingly, directing their application using the results of more limited processing. We show how to do this for retrospective video analysis by modeling a video using a chain graphical model and performing inference both to analyze the video and to direct processing. We apply our method to problems in background subtraction and face detection, and show in experiments that this leads to significant improvements over baseline algorithms.},
	keywords = {algorithms;digital, allocation;video, analysis;computer, background, detection;graphical, detection;resource, graphics;face, model;resource, processing;, processing;face, recognition;object, signal, subtraction;baseline, video},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2011.55},
	author = {Daozheng Chen and Bilgic,M. and Getoor, Lise and Jacobs, David W.}
}
@conference {13074,
	title = {A large-scale benchmark dataset for event recognition in surveillance video},
	booktitle = {Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on},
	year = {2011},
	month = {2011/06//},
	pages = {3153 - 3160},
	abstract = {We introduce a new large-scale video dataset designed to assess the performance of diverse visual event recognition algorithms with a focus on continuous visual event recognition (CVER) in outdoor areas with wide coverage. Previous datasets for action recognition are unrealistic for real-world surveillance because they consist of short clips showing one action by one individual [15, 8]. Datasets have been developed for movies [11] and sports [12], but, these actions and scene conditions do not apply effectively to surveillance videos. Our dataset consists of many outdoor scenes with actions occurring naturally by non-actors in continuously captured videos of the real world. The dataset includes large numbers of instances for 23 event types distributed throughout 29 hours of video. This data is accompanied by detailed annotations which include both moving object tracks and event examples, which will provide solid basis for large-scale evaluation. Additionally, we propose different types of evaluation modes for visual recognition tasks and evaluation metrics along with our preliminary experimental results. We believe that this dataset will stimulate diverse aspects of computer vision research and help us to advance the CVER tasks in the years ahead.},
	keywords = {algorithm;evaluation, CVER, databases;, databases;video, dataset;moving, event, metrics;large-scale, object, recognition, recognition;diverse, recognition;video, scenes;surveillance, surveillance;visual, tasks;computer, tracks;outdoor, video, video;computer, vision;continuous, vision;image, visual},
	doi = {10.1109/CVPR.2011.5995586},
	author = {Oh,Sangmin and Hoogs, A. and Perera,A. and Cuntoor, N. and Chen,Chia-Chih and Lee,Jong Taek and Mukherjee,S. and Aggarwal, JK and Lee,Hyungtae and Davis, Larry S. and Swears,E. and Wang,Xioyang and Ji,Qiang and Reddy,K. and Shah,M. and Vondrick,C. and Pirsiavash,H. and Ramanan,D. and Yuen,J. and Torralba,A. and Song,Bi and Fong,A. and Roy-Chowdhury, A. and Desai,M.}
}
@conference {18276,
	title = {Secure video processing: Problems and challenges},
	booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on},
	year = {2011},
	month = {2011/05//},
	pages = {5856 - 5859},
	abstract = {Secure signal processing is an emerging technology to enable signal processing tasks in a secure and privacy-preserving fashion. It has attracted a great amount of research attention due to the increasing demand to enable rich functionalities for private data stored online. Desirable functionalities may include search, analysis, clustering, etc. In this paper, we discuss the research issues and challenges in secure video processing with focus on the application of secure online video management. Video is different from text due to its large data volume and rich content diversity. To be practical, secure video processing requires efficient solutions that may involve a trade-off between security and complexity. We look at three representative video processing tasks and review existing techniques that can be applied. Many of the tasks do not have efficient solutions yet, and we discuss the challenges and research questions that need to be addressed.},
	keywords = {data;video, fashion;secure, management;secure, of, online, privacy-preserving, processing;, processing;security, signal, video},
	doi = {10.1109/ICASSP.2011.5947693},
	author = {Lu,Wenjun and Varna,A. and M. Wu}
}
@article {12494,
	title = {Face Recognition by Computers and Humans},
	journal = {Computer},
	volume = {43},
	year = {2010},
	month = {2010/02//},
	pages = {46 - 55},
	abstract = {This article talks about how the study of how humans perceive faces can be used to help design practical systems for face recognition. Besides applications related to identification and verification-such as access control, law enforcement, ID and licensing, and surveillance-face recognition has also proven useful in applications such as human-computer interaction, virtual reality, database retrieval, multimedia, and computer entertainment. Continuing research into face recognition will provide scientists and engineers with many vital projects, in areas such as homeland security, human-computer interaction, and numerous consumer applications. The areas we are considering pursuing are recognition from unconstrained video sequences, incorporating familiarity into algorithms, modeling effects of aging, and developing biologically plausible models for human face recognition ability.},
	keywords = {access, Computer, control;aging;computer, control;face, entertainment;database, interaction;national, interaction;unconstrained, reality;access, recognition;homeland, recognition;human, retrieval;face, security;, security;human, sequences;virtual, video},
	isbn = {0018-9162},
	doi = {10.1109/MC.2010.37},
	author = {Chellapa, Rama and Sinha, P. and Phillips,P.J.}
}
@conference {13108,
	title = {Assigning cameras to subjects in video surveillance systems},
	booktitle = {Robotics and Automation, 2009. ICRA {\textquoteright}09. IEEE International Conference on},
	year = {2009},
	month = {2009/05//},
	pages = {837 - 843},
	abstract = {We consider the problem of tracking multiple agents moving amongst obstacles, using multiple cameras. Given an environment with obstacles, and many people moving through it, we construct a separate narrow field of view video for as many people as possible, by stitching together video segments from multiple cameras over time. We employ a novel approach to assign cameras to people as a function of time, with camera switches when needed. The problem is modeled as a bipartite graph and the solution corresponds to a maximum matching. As people move, the solution is efficiently updated by computing an augmenting path rather than by solving for a new matching. This reduces computation time by an order of magnitude. In addition, solving for the shortest augmenting path minimizes the number of camera switches at each update. When not all people can be covered by the available cameras, we cluster as many people as possible into small groups, then assign cameras to groups using a minimum cost matching algorithm. We test our method using numerous runs from different simulators.},
	keywords = {agent, algorithm;multiple, assignment;computation, augmenting, cameras;video, cost, detection;video, graph;camera, MATCHING, matching;minimum, matching;target, path;bipartite, reduction;maximum, segment;video, Surveillance, surveillance;, system;graph, theory;image, TIME, tracking;obstacle, tracking;video, video},
	doi = {10.1109/ROBOT.2009.5152753},
	author = {El-Alfy,H. and Jacobs, David W. and Davis, Larry S.}
}
@article {12524,
	title = {Moving Object Verification in Airborne Video Sequences},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {19},
	year = {2009},
	month = {2009/01//},
	pages = {77 - 89},
	abstract = {This paper presents an end-to-end system for moving object verification in airborne video sequences. Using a sample selection module, the system first selects frames from a short sequence and stores them in an exemplar database. To handle appearance change due to potentially large aspect angle variations, a homography-based view synthesis method is then used to generate a novel view of each image in the exemplar database at the same pose as the testing object in each frame of a testing video segment. A rotationally invariant color matcher and a spatial-feature matcher based on distance transforms are combined using a weighted average rule to compare the novel view and the testing object. After looping over all testing frames, the set of match scores is passed to a temporal analysis module to examine the behavior of the testing object, and calculate a final likelihood. Very good verification performance is achieved over thousands of trials for both color and infrared video sequences using the proposed system.},
	keywords = {airborne, database;homography-based, databases;, matcher;color, matcher;image, matching;image, method;infrared, object, sequences;color, sequences;distance, sequences;moving, sequences;video, synthesis, system;exemplar, transforms;end-to-end, verification;spatial-feature, video, view},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2008.2009243},
	author = {Yue,Zhanfeng and Guarino, D. and Chellapa, Rama}
}
@article {18205,
	title = {Dynamic Resource Allocation for Robust Distributed Multi-Point Video Conferencing},
	journal = {Multimedia, IEEE Transactions on},
	volume = {10},
	year = {2008},
	month = {2008/08//},
	pages = {910 - 925},
	abstract = {This paper proposes a distributed multi-point video conferencing system over packet erasure channels, where the aggregation of multiple video streams and resource allocation are performed in a distributed manner. Video stream combiners, which are located in different geographical areas and serve as portals for conferees, aggregate incoming streams supplied by local users with other streams aggregated from nearby video stream combiners. A packet-division multiple-access (PDMA)-based error protection scheme is proposed to be performed at each video stream combiner to minimize the maximal expected video distortion among aggregated streams. The proposed error protection scheme for multi-stream aggregation also supports user preference. In order to deliver video streams to end users with different preferred quality, a consensus algorithm is proposed to adaptively perform resource allocation based on user preference. Simulation results show that the proposed multi-stream aggregation and error protection scheme has significant gains over traditional multi-stream error protection schemes for a multi-point video conferencing system.},
	keywords = {allocation;error, channels;packet-division, communication;, conferencing, conferencing;multi-access, distributed, dynamic, erasure, error, multiple-access-based, multipoint, Protection, resource, scheme;multi-point, scheme;robust, schemes;packet, streams;multistream, system;multiple, systems;teleconferencing;video, video},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2008.922846},
	author = {Chen,Meng and Su,Guan-Ming and M. Wu}
}
@conference {13118,
	title = {A Logic Framework for Sports Video Summarization Using Text-Based Semantic Annotation},
	booktitle = {Semantic Media Adaptation and Personalization, 2008. SMAP {\textquoteright}08. Third International Workshop on},
	year = {2008},
	month = {2008/12//},
	pages = {69 - 75},
	abstract = {Detection of semantic events in sports videos is an essential step towards video summarization. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. In this paper we present a novel sports video summarization framework using a combination of text, video and logic analysis. Parse trees are used to analyze structured and free-style text webcasting of sports games and extract the game{\^A}{\textquestiondown}s semantic events, such as goals and penalties in soccer games. Semantic events are then hierarchically arranged before being passed to a logic processing engine. The logic engine receives the summary preferences from the user and subsequently parses the event hierarchy to generate the game{\^A}{\textquestiondown}s summary according to the user{\^A}{\textquestiondown}s preferences. The proposed framework was applied to both soccer and basketball videos. We achieved an average accuracy of 98.6\% and 100\% on soccer and basketball videos, respectively.},
	keywords = {(mathematics);video, analysis;trees, annotation;Internet;broadcasting;sport;text, AUTOMATIC, detection;logic, engine;parse, event, PROCESSING, processing;, semantic, signal, summarization;text, trees;sports, video, Webcasting;text-based},
	doi = {10.1109/SMAP.2008.25},
	author = {Refaey,M.A. and Abd-Almageed, Wael and Davis, Larry S.}
}
@article {12542,
	title = {Machine Recognition of Human Activities: A Survey},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {18},
	year = {2008},
	month = {2008/11//},
	pages = {1473 - 1488},
	abstract = {The past decade has witnessed a rapid proliferation of video cameras in all walks of life and has resulted in a tremendous explosion of video content. Several applications such as content-based video annotation and retrieval, highlight extraction and video summarization require recognition of the activities occurring in the video. The analysis of human activities in videos is an area with increasingly important consequences from security and surveillance to entertainment and personal archiving. Several challenges at various levels of processing-robustness against errors in low-level processing, view and rate-invariant representations at midlevel processing and semantic representation of human activities at higher level processing-make this problem hard to solve. In this review paper, we present a comprehensive survey of efforts in the past couple of decades to address the problems of representation, recognition, and learning of human activities from video and related applications. We discuss the problem at two major levels of complexity: 1) "actions" and 2) "activities." "Actions" are characterized by simple motion patterns typically executed by a single human. "Activities" are more complex and involve coordinated actions among a small number of humans. We will discuss several approaches and classify them according to their ability to handle varying degrees of complexity as interpreted above. We begin with a discussion of approaches to model the simplest of action classes known as atomic or primitive actions that do not require sophisticated dynamical modeling. Then, methods to model actions with more complex dynamics are discussed. The discussion then leads naturally to methods for higher level representation of complex activities.},
	keywords = {activity;low-level, annotation;human, cameras;video, content-based, factors;image, processing;machine, processing;rate-invariant, recognition;image, recognition;midlevel, representation;image, representation;video, representations;semantic, retrieval;human, sequences;, summarization;content-based, video},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2008.2005594},
	author = {Turaga,P. and Chellapa, Rama and V.S. Subrahmanian and Udrea,O.}
}
@conference {13126,
	title = {Tracking Down Under: Following the Satin Bowerbird},
	booktitle = {Applications of Computer Vision, 2008. WACV 2008. IEEE Workshop on},
	year = {2008},
	month = {2008/01//},
	pages = {1 - 7},
	abstract = {Socio biologists collect huge volumes of video to study animal behavior (our collaborators work with 30,000 hours of video). The scale of these datasets demands the development of automated video analysis tools. Detecting and tracking animals is a critical first step in this process. However, off-the-shelf methods prove incapable of handling videos characterized by poor quality, drastic illumination changes, non-stationary scenery and foreground objects that become motionless for long stretches of time. We improve on existing approaches by taking advantage of specific aspects of this problem: by using information from the entire video we are able to find animals that become motionless for long intervals of time; we make robust decisions based on regional features; for different parts of the image, we tailor the selection of model features, choosing the features most helpful in differentiating the target animal from the background in that part of the image. We evaluate our method, achieving almost 83\% tracking accuracy on a more than 200,000 frame dataset of Satin Bowerbird courtship videos.},
	keywords = {analysis, behavior;animal, Bowerbird;animal, computing;feature, detection;animal, extraction;tracking;video, processing;zoology;, Satin, sciences, selection;behavioural, signal, tool;feature, tracking;automated, video},
	doi = {10.1109/WACV.2008.4544004},
	author = {Kembhavi,A. and Farrell,R. and Luo,Yuancheng and Jacobs, David W. and Duraiswami, Ramani and Davis, Larry S.}
}
@article {18181,
	title = {Collusion-Resistant Video Fingerprinting for Large User Group},
	journal = {Information Forensics and Security, IEEE Transactions on},
	volume = {2},
	year = {2007},
	month = {2007/12//},
	pages = {697 - 709},
	abstract = {Digital fingerprinting protects multimedia content from illegal redistribution by uniquely marking copies of the content distributed to users. Most existing multimedia fingerprinting schemes consider a user set on the scale of thousands. However, in such real-world applications as video-on-demand distribution, the number of potential users can be as many as 10-100 million. This large user size demands not only strong collusion resistance but also high efficiency in fingerprint construction, and detection, which makes most existing schemes incapable of being applied to these applications. A recently proposed joint coding and embedding fingerprinting framework provides a promising balance between collusion resistance, efficient construction, and detection, but several issues remain unsolved for applications involving a large group of users. In this paper, we explore how to employ the joint coding and embedding framework and develop practical algorithms to fingerprint video in such challenging settings as to accommodate more than ten million users and resist hundreds of users{\textquoteright} collusion. We investigate the proper code structure for large-scale fingerprinting and propose a trimming detection technique that can reduce the decoding computational complexity by more than three orders of magnitude at the cost of less than 0.5\% loss in detection probability under moderate to high watermark-to-noise ratios. Both analytic and experimental results show a high potential of joint coding and embedding to meet the needs of real-world large-scale fingerprinting applications.},
	keywords = {code, coding-embedding, coding;video, communication;video, complexity;decoding;digital, complexity;digital, computational, content;trimming, demand;watermarking;, DETECTION, distribution;computational, fingerprinting, fingerprinting;decoding, fingerprinting;joint, framework;large, group;multimedia, identification;multimedia, on, signatures;fingerprint, structure;collusion-resistant, technique;video-on-demand, user, video},
	isbn = {1556-6013},
	doi = {10.1109/TIFS.2007.908179},
	author = {He,Shan and M. Wu}
}
@conference {12583,
	title = {From Videos to Verbs: Mining Videos for Activities using a Cascade of Dynamical Systems},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 8},
	abstract = {Clustering video sequences in order to infer and extract activities from a single video stream is an extremely important problem and has significant potential in video indexing, surveillance, activity discovery and event recognition. Clustering a video sequence into activities requires one to simultaneously recognize activity boundaries (activity consistent subsequences) and cluster these activity subsequences. In order to do this, we build a generative model for activities (in video) using a cascade of dynamical systems and show that this model is able to capture and represent a diverse class of activities. We then derive algorithms to learn the model parameters from a video stream and also show how a single video sequence may be clustered into different clusters where each cluster represents an activity. We also propose a novel technique to build affine, view, rate invariance of the activity into the distance metric for clustering. Experiments show that the clusters found by the algorithm correspond to semantically meaningful activities.},
	keywords = {activities, clustering;image, clustering;video, extraction;dynamical, mining;video, processing;, sequence, sequences;pattern, signal, stream;video, systems;single, video},
	doi = {10.1109/CVPR.2007.383170},
	author = {Turaga, P.K. and Veeraraghavan,A. and Chellapa, Rama}
}
@conference {12594,
	title = {Joint Acoustic-Video Fingerprinting of Vehicles, Part II},
	booktitle = {Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on},
	volume = {2},
	year = {2007},
	month = {2007/04//},
	pages = {II-749 -II-752 - II-749 -II-752},
	abstract = {In this second paper, we first show how to estimate the wheelbase length of a vehicle using line metrology in video. We then address the vehicle fingerprinting problem using vehicle silhouettes and color invariants. We combine the acoustic metrology and classification results discussed in Part I with the video results to improve estimation performance and robustness. The acoustic video fusion is achieved in a Bayesian framework by assuming conditional independence of the observations of each modality. For the metrology density functions, Laplacian approximations are used for computational efficiency. Experimental results are given using field data},
	keywords = {acoustic-video, analysis;video, approximations;acoustic, Bayesian, colour, density, efficiency;joint, estimation;Bayes, fingerprinting;metrology, framework;Laplacian, functions;performance, fusion;color, identification;image, invariants;computational, methods;acoustic, metrology;acoustic, processing;, processing;fingerprint, signal, video},
	doi = {10.1109/ICASSP.2007.366344},
	author = {Cevher, V. and Guo, F. and Sankaranarayanan,A. C and Chellapa, Rama}
}
@article {18236,
	title = {Joint Uplink and Downlink Optimization for Real-Time Multiuser Video Streaming Over WLANs},
	journal = {Selected Topics in Signal Processing, IEEE Journal of},
	volume = {1},
	year = {2007},
	month = {2007/08//},
	pages = {280 - 294},
	abstract = {In this paper, a network-aware and source-aware video streaming system is proposed to support interactive multiuser communications within single-cell and multicell IEEE 802.11 networks. Unlike the traditional streaming video services, the strict delay constraints of an interactive video streaming system pose more challenges. These challenges include the heterogeneity of uplink and downlink channel conditions experienced by different users, the multiuser resource allocation of limited radio resources, the incorporation of the cross-layer design, and the diversity of content complexities exhibited by different video sequences. With the awareness of video content and network resources, the proposed system integrates cross-layer error protection mechanism and performs dynamic resource allocation across multiple users. We formulate the proposed system as to minimize the maximal end-to-end expected distortion received by all users, subject to maximal transmission power and delay constraints. To reduce the high dimensionality of the search space, fast multiuser algorithms are proposed to find the near-optimal solutions. Compared to the strategy without dynamically and jointly allocating bandwidth resource for uplinks and downlinks, the proposed framework outperforms by 2.18 7.95 dB in terms of the average received PSNR of all users and by 3.82 11.50 dB in terms of the lowest received PSNR among all users. Furthermore, the proposed scheme can provide more uniform video quality for all users and lower quality fluctuation for each received video sequence.},
	keywords = {802.11, allocation;image, allocation;real-time, communications;maximal, distortion;multiuser, end-to-end, error, expected, IEEE, LAN;, mechanism;downlink, multiuser, networks;WLAN;cross-layer, optimization;interactive, optimization;video, Protection, quality;video, resource, sequences;video, streaming, streaming;uplink, streaming;wireless, system;bandwidth, video},
	isbn = {1932-4553},
	doi = {10.1109/JSTSP.2007.901518},
	author = {Su,Guan-Ming and Han,Zhu and M. Wu and Liu,K. J.R}
}
@article {12587,
	title = {Target Tracking Using a Joint Acoustic Video System},
	journal = {Multimedia, IEEE Transactions on},
	volume = {9},
	year = {2007},
	month = {2007/06//},
	pages = {715 - 727},
	abstract = {In this paper, a multitarget tracking system for collocated video and acoustic sensors is presented. We formulate the tracking problem using a particle filter based on a state-space approach. We first discuss the acoustic state-space formulation whose observations use a sliding window of direction-of-arrival estimates. We then present the video state space that tracks a target{\textquoteright}s position on the image plane based on online adaptive appearance models. For the joint operation of the filter, we combine the state vectors of the individual modalities and also introduce a time-delay variable to handle the acoustic-video data synchronization issue, caused by acoustic propagation delays. A novel particle filter proposal strategy for joint state-space tracking is introduced, which places the random support of the joint filter where the final posterior is likely to lie. By using the Kullback-Leibler divergence measure, it is shown that the joint operation of the filter decreases the worst case divergence of the individual modalities. The resulting joint tracking filter is quite robust against video and acoustic occlusions due to our proposal strategy. Computer simulations are presented with synthetic and field data to demonstrate the filter{\textquoteright}s performance},
	keywords = {(numerical, acoustic, adaptive, appearance, approach;synchronization;time-delay, data, delay;acoustic, divergence;acoustic, estimate;joint, estimation;hidden, feature, filter;sliding, Filtering, fusion;multitarget, fusion;synchronisation;target, highways;direction-of-arrival, Kullback-Leibler, methods);sensor, model;particle, processing;, processing;automated, propagation, removal;optical, signal, system;multimodal, tracking;acoustic, tracking;direction-of-arrival, tracking;occlusion;online, tracking;particle, tracking;video, variable;visual, video, window;state-space},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2007.893340},
	author = {Cevher, V. and Sankaranarayanan,A. C and McClellan, J.H. and Chellapa, Rama}
}
@conference {18186,
	title = {Cross-Path PDMA-Based Error Protection for Streaming Multiuser Video over Multiple Paths},
	booktitle = {Image Processing, 2006 IEEE International Conference on},
	year = {2006},
	month = {2006/10//},
	pages = {21 - 24},
	abstract = {In this paper, we consider aggregating multiple video streams and transmitting the merged stream over multiple error-prone paths. We propose a novel multi-stream error protection scheme based on packet division multiplexing access (PDMA) and cross-path forward error coding. Compared with the traditional time division multiplexing access (TDMA)-based error protection scheme, the proposed scheme outperforms 1.43 1.88 dB for the averaged PSNR of all received streams},
	keywords = {access;error, codes;forward, coding;multiple, coding;video, correction, correction;multi-access, division, error, error-prone, forward, multiplexing, path;multistream, PDMA;cross-path, Protection, scheme;multiuser, streaming;, streaming;packet, systems;video, video},
	doi = {10.1109/ICIP.2006.313151},
	author = {Su,Guan-Ming and Chen,Meng and M. Wu}
}
@article {18253,
	title = {Multiuser cross-layer resource allocation for video transmission over wireless networks},
	journal = {Network, IEEE},
	volume = {20},
	year = {2006},
	month = {2006/04//march},
	pages = {21 - 27},
	abstract = {With the advancement of video-compression technology and the wide deployment of wireless networks, there is an increasing demand for wireless video communication services, and many design challenges remain to be overcome. In this article, we discuss how to dynamically allocate resources according to the changing environments and requirements, so as to improve the overall system performance and ensure individual quality of service (QoS). Specifically, we consider two aspects with regard to design issues: cross-layer design, which jointly optimizes resource utilization from the physical layer to the application layer, and multiuser diversity, which explores source and channel heterogeneity for different users. We study how to efficiently transmit multiple video streams, encoded by current and future video codecs, over resource-limited wireless networks such as 3G/4G cellular system and future wireless local/metropolitan area networks (WLANs/WMANs)},
	keywords = {3G, allocation;multiuser, allocation;video, cellular, channels;quality, codecs;video, coding;video, communication;4G, communication;data, compression;diversity, cross-layer, diversity;physical, layer;multiple, layer;quality, mobile, networks;3G, of, reception;multiuser, resource, service;resource, service;video, streaming;, streams;multiuser, system;4G, system;QoS;application, technology;wireless, transmission;video-compression, video},
	isbn = {0890-8044},
	doi = {10.1109/MNET.2006.1607892},
	author = {Su,Guan-Ming and Man,Zhu and M. Wu and Liu,K. J.R}
}
@article {18159,
	title = {A Scalable Multiuser Framework for Video Over OFDM Networks: Fairness and Efficiency},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {16},
	year = {2006},
	month = {2006/10//},
	pages = {1217 - 1231},
	abstract = {In this paper, we propose a framework to transmit multiple scalable video programs over downlink multiuser orthogonal frequency division multiplex (OFDM) networks in real time. The framework explores the scalability of the video codec and multidimensional diversity of multiuser OFDM systems to achieve the optimal service objectives subject to constraints on delay and limited system resources. We consider two essential service objectives, namely, the fairness and efficiency. Fairness concerns the video quality deviation among users who subscribe the same quality of service, and efficiency relates to how to attain the highest overall video quality using the available system resources. We formulate the fairness problem as minimizing the maximal end-to-end distortion received among all users and the efficiency problem as minimizing total end-to-end distortion of all users. Fast suboptimal algorithms are proposed to solve the above two optimization problems. The simulation results demonstrated that the proposed fairness algorithm outperforms a time division multiple (TDM) algorithm by 0.5 3 dB in terms of the worst received video quality among all users. In addition, the proposed framework can achieve a desired tradeoff between fairness and efficiency. For achieving the same average video quality among all users, the proposed framework can provide fairer video quality with 1 1.8 dB lower PSNR deviation than a TDM algorithm},
	keywords = {algorithm;video, codec;video, coding;video, communication;, deviation;downlink, deviation;OFDM, distortion;multidimensional, diversity;multiple, division, end-to-end, framework;time, Frequency, modulation;diversity, multiple, multiplex, multiuser, network;efficiency, networks;video, objectives;optimization, of, OFDM, orthogonal, over, problem;fairness, problem;maximal, problems;quality, programs;multiuser, PSNR, QUALITY, reception;image, resolution;optimisation;quality, scalable, service, service;scalable, service;video, systems;optimal, video},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2006.883513},
	author = {Su,Guan-Ming and Han,Zhu and M. Wu and Liu,K. J.R}
}
@conference {12609,
	title = {Stabilization and Mosaicing of Airborne Videos},
	booktitle = {Image Processing, 2006 IEEE International Conference on},
	year = {2006},
	month = {2006/10//},
	pages = {345 - 348},
	abstract = {We present an algorithm for stabilizing low-quality and low-resolution video sequences obtained from UAVs and MAVs flying over a predominantly planar terrain. The problem is important for the processing of videos captured from airborne platforms where most of the image region gives little information about the image-motion. The algorithm consists of approximately aligning the images using phase correlation, then refining the transformation parameters using available optical flow measurements and finally performing a minimization of the image difference by carefully selecting the image regions to make the iterations converge. In the second part of the paper, we describe an algorithm for camera ego-motion estimation by incorporating available metadata along with the video sequence. The availability of metadata such as IMU measurements provides a good initial solution for the camera orientation and helps the iterations converge faster by reducing the search space},
	keywords = {airborne, analysis;image, cameras;, convergence;low-resolution, ego-motion, estimation;iterations, flow, measurement;video, mosaicing;camera, MOTION, resolution;image, segmentation;image, sequence;optical, sequences;video, stabilization;image, video, Videos},
	doi = {10.1109/ICIP.2006.313164},
	author = {Ramachandran, M. and Chellapa, Rama}
}
@article {18208,
	title = {Efficient bandwidth resource allocation for low-delay multiuser video streaming},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {15},
	year = {2005},
	month = {2005/09//},
	pages = {1124 - 1137},
	abstract = {This paper studies efficient bandwidth resource allocation for streaming multiple MPEG-4 fine granularity scalability (FGS) video programs to multiple users. We begin with a simple single-user scenario and propose a rate-control algorithm that has low delay and achieves an excellent tradeoff between the average visual distortion and the quality fluctuation. The proposed algorithm employs two weight factors for adjusting the tradeoff, and the optimal choice of these factors is derived. We then extend to the multiuser case and propose a dynamic resource allocation algorithm with low delay and low computational complexity. By exploring the variations in the scene complexity of video programs as well as dynamically and jointly distributing the available system resources among users, our proposed algorithm provides low fluctuation of quality for each user, and can support consistent or differentiated quality among all users to meet applications{\textquoteright} needs. Experimental results show that compared to traditional look-ahead sliding-window approaches, our algorithm can achieve comparable visual quality and channel utilization at a much lower cost of delay, computation, and storage.},
	keywords = {algorithm;, allocation, allocation;, approaches;, average, Bandwidth, channel, channels;, coding;, complexity;, computational, control;, distortion;, dynamic, efficient, fine, fluctuation;, granularity, look-ahead, low-delay, MPEG-4, multiple, multiuser, QUALITY, quality;, rate-control, resource, scalability, scenario;, single-user, sliding-window, streaming;, Telecommunication, utilization;, video, visual},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2005.852626},
	author = {Su,Guan-Ming and M. Wu}
}
@conference {13197,
	title = {Fast illumination-invariant background subtraction using two views: error analysis, sensor placement and applications},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {1071 - 1078 vol. 1 - 1071 - 1078 vol. 1},
	abstract = {Background modeling and subtraction to detect new or moving objects in a scene is an important component of many intelligent video applications. Compared to a single camera, the use of multiple cameras leads to better handling of shadows, specularities and illumination changes due to the utilization of geometric information. Although the result of stereo matching can be used as the feature for detection, it has been shown that the detection process can be made much faster by a simple subtraction of the intensities observed at stereo-generated conjugate pairs in the two views. The methodology however, suffers from false and missed detections due to some geometric considerations. In this paper, we perform a detailed analysis of such errors. Then, we propose a sensor configuration that eliminates false detections. Algorithms are also proposed that effectively eliminate most detection errors due to missed detections, specular reflections and objects being geometrically close to the background. Experiments on several scenes illustrate the utility and enhanced performance of the proposed approach compared to existing techniques.},
	keywords = {analysis;, application;, background, cameras;, configuration;, DETECTION, detection;, error, error;, extraction;, false, feature, handling;, illumination-invariance;, image, intelligent, matching;, modeling;, object, placement;, processing;, sensor, sensors;, shadow, stereo, subtraction;, video},
	doi = {10.1109/CVPR.2005.155},
	author = {Lim,Ser-Nam and Mittal,A. and Davis, Larry S. and Paragios,N.}
}
@conference {18237,
	title = {Joint uplink and downlink optimization for video conferencing over wireless LAN},
	booktitle = {Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP {\textquoteright}05). IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/03//},
	pages = {ii/1101 - ii/1104 Vol. 2 - ii/1101 - ii/1104 Vol. 2},
	abstract = {A real-time video conferencing framework is proposed for multiple conferencing pairs by jointly considering the uplink and downlink conditions within IEEE 802.11 networks. We formulate this system so as to minimize the maximal end-to-end expected distortion received by all users by selecting the PHY modes and transmission time. Compared with the strategy of individually optimizing uplink and downlink, the proposed framework outperforms by 3.67-8.65 dB for the average received PSNR among all users.},
	keywords = {802.11, conferencing, conferencing;, distortion;, end-to-end, expected, IEEE, joint, LAN;, maximal, minimisation;, modes;, multiple, networks;, optimization;, pairs;, PHY, PSNR;, real-time, teleconferencing;, time;, transmission, uplink-downlink, video, wireless},
	doi = {10.1109/ICASSP.2005.1415601},
	author = {Su,Guan-Ming and Han,Zhu and M. Wu and Liu,K. J.R}
}
@conference {13198,
	title = {Kernel-based Bayesian filtering for object tracking},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {227 - 234 vol. 1 - 227 - 234 vol. 1},
	abstract = {Particle filtering provides a general framework for propagating probability density functions in nonlinear and non-Gaussian systems. However, the algorithm is based on a Monte Carlo approach and sampling is a problematic issue, especially for high dimensional problems. This paper presents a new kernel-based Bayesian filtering framework, which adopts an analytic approach to better approximate and propagate density functions. In this framework, the techniques of density interpolation and density approximation are introduced to represent the likelihood and the posterior densities by Gaussian mixtures, where all parameters such as the number of mixands, their weight, mean, and covariance are automatically determined. The proposed analytic approach is shown to perform sampling more efficiently in high dimensional space. We apply our algorithm to real-time tracking problems, and demonstrate its performance on real video sequences as well as synthetic examples.},
	keywords = {approach;, approximation;, Bayes, Bayesian, Carlo, density, detection;, filtering;, functions;, Gaussian, interpolation;, kernel-based, methods;, mixtures;, Monte, nonGaussian, nonlinear, object, particle, probability, probability;, processes;, recognition;, sampling, sampling;, sequences;, system;, tracking;, video},
	doi = {10.1109/CVPR.2005.199},
	author = {Han,Bohyung and Zhu,Ying and Comaniciu, D. and Davis, Larry S.}
}
@conference {12665,
	title = {Moving Object Segmentation and Dynamic Scene Reconstruction Using Two Frames},
	booktitle = {Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP {\textquoteright}05). IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005//18/23},
	pages = {705 - 708},
	keywords = {3D, analysis;, constraints;, dynamic, ego-motion, estimation;, flow, image, images;, independent, INTENSITY, least, mean, median, method;, methods;, model;, MOTION, motion;, moving, object, of, parallax, parallax;, parametric, processing;, reconstruction;, scene, segmentation;, signal, squares, squares;, static, structure;, subspace, surface, translational, two-frame, unconstrained, video},
	doi = {10.1109/ICASSP.2005.1415502},
	author = {Agrawala, Ashok K. and Chellapa, Rama}
}
@conference {12652,
	title = {Tracking objects in video using motion and appearance models},
	booktitle = {Image Processing, 2005. ICIP 2005. IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/09//},
	pages = {II - 394-7 - II - 394-7},
	abstract = {This paper proposes a visual tracking algorithm that combines motion and appearance in a statistical framework. It is assumed that image observations are generated simultaneously from a background model and a target appearance model. This is different from conventional appearance-based tracking, that does not use motion information. The proposed algorithm attempts to maximize the likelihood ratio of the tracked region, derived from appearance and background models. Incorporation of motion in appearance based tracking provides robust tracking, even when the target violates the appearance model. We show that the proposed algorithm performs well in tracking targets efficiently over long time intervals.},
	keywords = {algorithm;, analysis;, appearance, background, estimation;, image, likelihood, maximum, model;, models;, MOTION, object, processing;, signal, target, tracking, tracking;, video, visual},
	doi = {10.1109/ICIP.2005.1530075},
	author = {Sankaranarayanan,A. C and Chellapa, Rama and Qinfen Zheng}
}
@conference {13191,
	title = {VidMAP: video monitoring of activity with Prolog},
	booktitle = {Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on},
	year = {2005},
	month = {2005/09//},
	pages = {224 - 229},
	abstract = {This paper describes the architecture of a visual surveillance system that combines real time computer vision algorithms with logic programming to represent and recognize activities involving interactions amongst people, packages and the environments through which they move. The low level computer vision algorithms log primitive events of interest as observed facts, while the higher level Prolog based reasoning engine uses these facts in conjunction with predefined rules to recognize various activities in the input video streams. The system is illustrated in action on a multi-camera surveillance scenario that includes both security and safety violations.},
	keywords = {activities, algorithms;, based, Computer, computerised, engine;, higher, image, level, Logic, monitoring;, multicamera, processing;, programming;, Prolog, PROLOG;, reasoning, recognition;, scenario;, signal, streaming;, streams;, Surveillance, surveillance;, system;, video, VISION, vision;, visual},
	doi = {10.1109/AVSS.2005.1577271},
	author = {Shet,V. D and Harwood,D. and Davis, Larry S.}
}
@conference {12703,
	title = {Appearance-based tracking and recognition using the 3D trilinear tensor},
	booktitle = {Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP {\textquoteright}04). IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/05//},
	pages = {iii - 613-16 vol.3 - iii - 613-16 vol.3},
	abstract = {The paper presents an appearance-based adaptive algorithm for simultaneous tracking and recognition by generalizing the transformation model to 3D perspective transformation. A trilinear tensor operator is used to represent the 3D geometrical structure. The tensor is estimated by predicting the corresponding points using the existing affine-transformation based algorithm. The estimated tensor is used to synthesize novel views to update the appearance templates. Some experimental results using airborne video are presented.},
	keywords = {3D, adaptive, affine-transformation, airborne, algorithm;, appearance, appearance-based, based, estimation;, geometrical, image, mathematical, novel, object, operator;, operators;, perspective, prediction;, processing;, recognition;, representation;, signal, structure, synthesis;, template, tensor, tensor;, tensors;, tracking;, transformation;, trilinear, updating;, video, video-based, video;, view},
	doi = {10.1109/ICASSP.2004.1326619},
	author = {Jie Shao and Zhou,S. K and Chellapa, Rama}
}
@conference {13213,
	title = {Background modeling and subtraction by codebook construction},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {5},
	year = {2004},
	month = {2004/10//},
	pages = {3061 - 3064 Vol. 5 - 3061 - 3064 Vol. 5},
	abstract = {We present a new fast algorithm for background modeling and subtraction. Sample background values at each pixel are quantized into codebooks which represent a compressed form of background model for a long image sequence. This allows us to capture structural background variation due to periodic-like motion over a long period of time under limited memory. Our method can handle scenes containing moving backgrounds or illumination variations (shadows and highlights), and it achieves robust detection for compressed videos. We compared our method with other multimode modeling techniques.},
	keywords = {(signal);, analysis;, background, codebook, coding;, colour, compression;, construction;, data, image, modeling, modeling;, MOTION, multimode, quantisation, representation;, sequence;, sequences;, subtraction;, technique;, video},
	doi = {10.1109/ICIP.2004.1421759},
	author = {Kim,Kyungnam and Chalidabhongse,T.H. and Harwood,D. and Davis, Larry S.}
}
@conference {18200,
	title = {Distortion management of real-time MPEG-4 video over downlink multicode CDMA networks},
	booktitle = {Communications, 2004 IEEE International Conference on},
	volume = {5},
	year = {2004},
	month = {2004/06//},
	pages = {3071 - 3075 Vol.5 - 3071 - 3075 Vol.5},
	abstract = {In this paper, a protocol is designed to manage source rate/channel coding rate adaptation, code allocation, and power control to transmit real-time MPEG-4 FGS video over downlink multicode CDMA networks. We develop a fast adaptive scheme of distortion management to reduce the overall distortion received by all users subject, to the limited number of codes and maximal transmitted power. Compared with a modified greedy method in literature, our proposed algorithm can reduce the overall system{\textquoteright}s distortion by at least 45\%.},
	keywords = {access;, adaptation;, allocation;, CDMA, channel, code, coding, coding;, combined, communication;, compression;, control;, data, distortion, division, downlink, links;, management;, MPEG-4, multicode, multiple, networks;, power, radio, rate, real-time, resource, source, source-channel, video, video;, visual},
	doi = {10.1109/ICC.2004.1313096},
	author = {Su,Guan-Ming and Han,Zhu and Kwasinski,A. and M. Wu and Liu,K. J.R and Farvardin,N.}
}
@conference {18201,
	title = {Dynamic distortion control for 3-D embedded wavelet video over multiuser OFDM networks},
	booktitle = {Global Telecommunications Conference, 2004. GLOBECOM {\textquoteright}04. IEEE},
	volume = {2},
	year = {2004},
	month = {2004/12/03/nov},
	pages = {650 - 654 Vol.2 - 650 - 654 Vol.2},
	abstract = {In this paper, we propose a system to transmit multiple 3D embedded wavelet video programs over downlink multiuser OFDM. We consider the fairness among users and formulate the problem as minimizing the users{\textquoteright} maximal distortion subject to power, rate, and subcarrier constraints. By exploring frequency, time, and multiuser diversity in OFDM and flexibility of the 3D embedded wavelet video codec, the proposed algorithm can achieve fair video qualities among all users. Compared to a scheme similar to the current multiuser OFDM standard (IEEE 802.11a), the proposed scheme outperforms it by 1-5 dB on the worst received PSNR among all users and has much smaller PSNR deviation.},
	keywords = {3D, 802.11a;, channels;, codec;, codecs;, communication;, control;, deviation;, distortion, diversity, diversity;, downlink, dynamic, embedded, fairness;, Frequency, IEEE, LAN;, maximal, minimax, minimization;, modulation;, multimedia, multiuser, OFDM, OFDM;, PSNR, rate, reception;, streaming;, systems;, techniques;, theory;, TIME, transforms;, video, video;, wavelet, wireless},
	doi = {10.1109/GLOCOM.2004.1378042},
	author = {Su,Guan-Ming and Han,Zhu and M. Wu and Liu,K. J.R}
}
@conference {18207,
	title = {Efficient bandwidth resource allocation for low-delay multiuser MPEG-4 video transmission},
	booktitle = {Communications, 2004 IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/06//},
	pages = {1308 - 1312 Vol.3 - 1308 - 1312 Vol.3},
	abstract = {An efficient bandwidth resource allocation algorithm with low delay and low fluctuation of quality to transmit multiple MPEG-4 fine granularity scalability (FGS) video programs to multiple users is proposed in this paper. By exploring the variation in the scene complexity of each video program and jointly redistributing available system resources among users, our proposed algorithm provides low fluctuation of quality for each user and consistent quality among all users. Experimental results show that compared to a traditional look-ahead sliding-window approach, our scheme can achieve comparable perceptual quality and channel utilization at a much lower cost of delay, computation, and storage.},
	keywords = {algorithm;, allocation, allocation;, approach;, Bandwidth, broadband, channel, channels;, coding;, delays;, expert, FGS;, fine, granularity, group;, look-ahead, moving, MPEG-4, multiuser, networks;, of, picture, program;, QUALITY, resource, scalability;, service;, sliding-window, transmission;, utilization;, video},
	doi = {10.1109/ICC.2004.1312724},
	author = {Su,Guan-Ming and M. Wu}
}
@conference {13212,
	title = {A fine-structure image/video quality measure using local statistics},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {5},
	year = {2004},
	month = {2004/10//},
	pages = {3535 - 3538 Vol. 5 - 3535 - 3538 Vol. 5},
	abstract = {An objective no-reference measure is presented to assess line-structure image/video quality. It was designed to measure image/video quality for video surveillance applications, especially for background modeling and foreground object detection. The proposed measure using local statistics reflects image degradation well in terms of noise and blur. The experimental results on a background subtraction algorithm validate the usefulness of the proposed measure, by showing its correlation with the algorithm{\textquoteright}s performance.},
	keywords = {algorithm;, background, degradation;, detection;, foreground, image, line-structure, local, measure;, modeling;, no-reference, object, objective, processing;, QUALITY, signal, statistics;, subtraction, surveillance;, video},
	doi = {10.1109/ICIP.2004.1421879},
	author = {Kim,Kyungnam and Davis, Larry S.}
}
@conference {12683,
	title = {Multiple view tracking of humans modelled by kinematic chains},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1009 - 1012 Vol.2 - 1009 - 1012 Vol.2},
	abstract = {We use a kinematic chain to model human body motion. We estimate the kinematic chain motion parameters using pixel displacements calculated from video sequences obtained from multiple calibrated cameras to perform tracking. We derive a linear relation between the 2D motion of pixels in terms of the 3D motion parameters of various body parts using a perspective projection model for the cameras, a rigid body motion model for the base body and the kinematic chain model for the body parts. An error analysis of the estimator is provided, leading to an iterative algorithm for calculating the motion parameters from the pixel displacements. We provide experimental results to demonstrate the accuracy of our formulation. We also compare our iterative algorithm to the noniterative algorithm and discuss its robustness in the presence of noise.},
	keywords = {3D, algorithm;, analysis;, body, calibrated, cameras;, chain, displacement;, error, estimation;, human, image, iterative, kinematic, kinematics;, methods;, model;, MOTION, motion;, multiple, parameters;, perspective, Pixel, processing;, projection, sequences;, signal, tracking;, video, view},
	doi = {10.1109/ICIP.2004.1419472},
	author = {Sundaresan, A. and Chellapa, Rama and RoyChowdhury, R.}
}
@conference {17802,
	title = {The priority curve algorithm for video summarization},
	booktitle = {Proceedings of the 2nd ACM international workshop on Multimedia databases},
	series = {MMDB {\textquoteright}04},
	year = {2004},
	month = {2004///},
	pages = {28 - 35},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In this paper, we introduce the concept of a priority curve associated with a video. We then provide an algorithm that can use the priority curve to create a summary (of a desired length) of any video. The summary thus created exhibits nice continuity properties and also avoids repetition. We have implemented the priority curve algorithm (PCA) and compared it with other summarization algorithms in the literature. We show that PCA is faster than existing algorithms and also produces better quality summaries. The quality of summaries was evaluated by a group of 200 students in Naples, Italy, who watched soccer videos. We also briefly describe a soccer video summarization system we have built on using the PCA architecture and various (classical) image processing algorithms.},
	keywords = {probabilistic, Summarization, system, video},
	isbn = {1-58113-975-6},
	doi = {10.1145/1032604.1032611},
	url = {http://doi.acm.org/10.1145/1032604.1032611},
	author = {Fayzullin,M. and V.S. Subrahmanian and Albanese, M. and Picariello, A.}
}
@conference {12695,
	title = {Probabilistic identity characterization for face recognition},
	booktitle = {Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on},
	volume = {2},
	year = {2004},
	month = {2004/07/02/june},
	pages = {II-805 - II-812 Vol.2 - II-805 - II-812 Vol.2},
	abstract = {We present a general framework for characterizing the object identity in a single image or a group of images with each image containing a transformed version of the object, with applications to face recognition. In terms of the transformation, the group is made of either many still images or frames of a video sequence. The object identity is either discrete- or continuous-valued. This probabilistic framework integrates all the evidence of the set and handles the localization problem, illumination and pose variations through subspace identity encoding. Issues and challenges arising in this framework are addressed and efficient computational schemes are presented. Good face recognition results using the PIE database are reported.},
	keywords = {characterization;, database, database;, encoding;, Face, identity, identity;, image, localization, management, object, PIE, probabilistic, problem;, recognition;, sequence;, sequences;, subspace, systems;, video},
	doi = {10.1109/CVPR.2004.1315247},
	author = {Zhou,S. K and Chellapa, Rama}
}
@conference {12702,
	title = {Robust two-camera tracking using homography},
	booktitle = {Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP {\textquoteright}04). IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/05//},
	pages = {iii - 1-4 vol.3 - iii - 1-4 vol.3},
	abstract = {The paper introduces a two view tracking method which uses the homography relation between the two views to handle occlusions. An adaptive appearance-based model is incorporated in a particle filter to realize robust visual tracking. Occlusion is detected using robust statistics. When there is occlusion in one view, the homography from this view to other views is estimated from previous tracking results and used to infer the correct transformation for the occluded view. Experimental results show the robustness of the two view tracker.},
	keywords = {Carlo, filter;, filters;, frame, framework;, homography;, image, method;, methods;, Monte, nonlinear, occlusions;, optical, particle, processing;, robust, sequences;, sequential, signal, statistics;, tracking, tracking;, two, two-camera, video, view, visual},
	doi = {10.1109/ICASSP.2004.1326466},
	author = {Yue,Zhanfeng and Zhou,S. K and Chellapa, Rama}
}
@conference {18278,
	title = {Security evaluation for communication-friendly encryption of multimedia},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {1},
	year = {2004},
	month = {2004/10//},
	pages = {569 - 572 Vol. 1 - 569 - 572 Vol. 1},
	abstract = {This paper addresses the access control issues unique to multimedia, by using a joint signal processing and cryptographic approach to multimedia encryption. Based on three atomic encryption primitives, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. We also propose a set of multimedia-specific security metrics to quantify the security against approximation attacks and to complement the existing notion of generic data security. The resulting system can provide superior performance to both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and communication friendliness.},
	keywords = {access, approximation, atomic, attacks;, bitrate, coding;, communication-friendly, communication;, control;, cryptography;, data, encryption, encryption;, generic, joint, method;, metrics;, multimedia, multimedia-specific, overhead;, primitives;, processing/cryptographic, Security, security;, signal, system;, Telecommunication, video},
	doi = {10.1109/ICIP.2004.1418818},
	author = {Mao,Yinian and M. Wu}
}
@conference {12684,
	title = {Simultaneous background and foreground modeling for tracking in surveillance video},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1053 - 1056 Vol.2 - 1053 - 1056 Vol.2},
	abstract = {We present a stochastic tracking algorithm for surveillance video where targets are dim and at low resolution. The algorithm builds motion models for both background and foreground by integrating motion and intensity information. Some other merits of the algorithm include adaptive selection of feature points for scene description and defining proper cost functions for displacement estimation. The experimental results show tracking robustness and precision in a challenging video sequences.},
	keywords = {algorithm;, analysis;, background-foreground, displacement, estimation;, image, information;, INTENSITY, modeling;, MOTION, processes;, processing;, resolution;, sequences;, signal, Stochastic, Surveillance, surveillance;, tracking, tracking;, video},
	doi = {10.1109/ICIP.2004.1419483},
	author = {Shao, J. and Zhou,S. K and Chellapa, Rama}
}
@conference {12694,
	title = {A system identification approach for video-based face recognition},
	booktitle = {Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
	volume = {4},
	year = {2004},
	month = {2004/08//},
	pages = {175 - 178 Vol.4 - 175 - 178 Vol.4},
	abstract = {The paper poses video-to-video face recognition as a dynamical system identification and classification problem. We model a moving face as a linear dynamical system whose appearance changes with pose. An autoregressive and moving average (ARMA) model is used to represent such a system. The choice of ARMA model is based on its ability to take care of the change in appearance while modeling the dynamics of pose, expression etc. Recognition is performed using the concept of sub space angles to compute distances between probe and gallery video sequences. The results obtained are very promising given the extent of pose, expression and illumination variation in the video data used for experiments.},
	keywords = {and, autoregressive, average, dynamical, Face, gallery, identification;, image, linear, model;, moving, processes;, processing;, recognition;, sequences;, signal, system, system;, video, video-based},
	doi = {10.1109/ICPR.2004.1333732},
	author = {Aggarwal,G. and Chowdhury, A.K.R. and Chellapa, Rama}
}
@conference {12705,
	title = {Vehicle detection and tracking using acoustic and video sensors},
	booktitle = {Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP {\textquoteright}04). IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/05//},
	pages = {iii - 793-6 vol.3 - iii - 793-6 vol.3},
	abstract = {Multimodal sensing has attracted much attention in solving a wide range of problems, including target detection, tracking, classification, activity understanding, speech recognition, etc. In surveillance applications, different types of sensors, such as video and acoustic sensors, provide distinct observations of ongoing activities. We present a fusion framework using both video and acoustic sensors for vehicle detection and tracking. In the detection phase, a rough estimate of target direction-of-arrival (DOA) is first obtained using acoustic data through beam-forming techniques. This initial DOA estimate designates the approximate target location in video. Given the initial target position, the DOA is refined by moving target detection using the video data. Markov chain Monte Carlo techniques are then used for joint audio-visual tracking. A novel fusion approach has been proposed for tracking, based on different characteristics of audio and visual trackers. Experimental results using both synthetic and real data are presented. Improved tracking performance has been observed by fusing the empirical posterior probability density functions obtained using both types of sensors.},
	keywords = {acoustic, applications;, audio, audio-visual, beam-forming, Carlo, chain, density, detection;, direction-of-arrival, DOA, empirical, estimation;, framework;, functions;, fusion, fusion;, joint, Markov, methods;, Monte, moving, multimodal, object, optical, posterior, probability, probability;, processes;, processing;, sensing;, sensor, sensors;, signal, Surveillance, surveillance;, systems;, target, techniques;, tracking;, vehicle, video},
	doi = {10.1109/ICASSP.2004.1326664},
	author = {Chellapa, Rama and Qian,Gang and Qinfen Zheng}
}
@article {12699,
	title = {Wide baseline image registration with application to 3-D face modeling},
	journal = {Multimedia, IEEE Transactions on},
	volume = {6},
	year = {2004},
	month = {2004/06//},
	pages = {423 - 434},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles is a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, three-dimensional (3-D) model alignment, creation of panoramic views, etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching two-dimensional (2-D) shapes of the different features of the face (e.g., eyes, nose etc.). A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellation of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3-D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, baseline, biometrics;, Computer, configuration;, correspondence, doubly, error, extraction;, Face, feature, holistic, image, matching;, matrix;, minimization;, modeling;, models;, normalization, probability, probability;, procedure;, processes;, processing;, recognition;, registration;, representation;, sequences;, shapes;, Sinkhorn, spatial, statistics;, Stochastic, video, vision;, wide},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2004.827511},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama and Keaton, T.}
}
@conference {12729,
	title = {Activity recognition using the dynamics of the configuration of interacting objects},
	booktitle = {Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on},
	volume = {2},
	year = {2003},
	month = {2003/06//},
	pages = {II - 633-40 vol.2 - II - 633-40 vol.2},
	abstract = {Monitoring activities using video data is an important surveillance problem. A special scenario is to learn the pattern of normal activities and detect abnormal events from a very low resolution video where the moving objects are small enough to be modeled as point objects in a 2D plane. Instead of tracking each point separately, we propose to model an activity by the polygonal {\textquoteright}shape{\textquoteright} of the configuration of these point masses at any time t, and its deformation over time. We learn the mean shape and the dynamics of the shape change using hand-picked location data (no observation noise) and define an abnormality detection statistic for the simple case of a test sequence with negligible observation noise. For the more practical case where observation (point locations) noise is large and cannot be ignored, we use a particle filter to estimate the probability distribution of the shape given the noisy observations up to the current time. Abnormality detection in this case is formulated as a change detection problem. We propose a detection strategy that can detect both {\textquoteright}drastic{\textquoteright} and {\textquoteright}slow{\textquoteright} abnormalities. Our framework can be directly applied for object location data obtained using any type of sensors - visible, radar, infrared or acoustic.},
	keywords = {2D, abnormal, abnormality, abnormality;, acoustic, activity, analysis;, change;, Computer, configuration, configuration;, data;, DETECTION, detection;, distribution;, drastic, dynamics;, event;, filter;, hand-picked, image, infrared, interacting, learning;, location, low, mean, model;, monitoring;, MOTION, moving, noise;, noisy, object, object;, observation, observation;, particle, pattern, plane;, point, polygonal, probability, probability;, problem;, processing;, radar, recognition;, resolution, sensor;, sensors;, sequence;, SHAPE, shape;, signal, slow, statistic;, strategy;, Surveillance, surveillance;, target, test, tracking;, video, video;, visible, vision;},
	doi = {10.1109/CVPR.2003.1211526},
	author = {Vaswani, N. and RoyChowdhury, A. and Chellapa, Rama}
}
@conference {12723,
	title = {Adaptive visual tracking and recognition using particle filters},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {2},
	year = {2003},
	month = {2003/07//},
	pages = {II - 349-52 vol.2 - II - 349-52 vol.2},
	abstract = {This paper presents an improved method for simultaneous tracking and recognition of human faces from video, where a time series model is used to resolve the uncertainties in tracking and recognition. The improvements mainly arise from three aspects: (i) modeling the inter-frame appearance changes within the video sequence using an adaptive appearance model and an adaptive-velocity motion model; (ii) modeling the appearance changes between the video frames and gallery images by constructing intra- and extra-personal spaces; and (iii) utilization of the fact that the gallery images are in frontal views. By embedding them in a particle filter, we are able to achieve a stabilized tracker and an accurate recognizer when confronted by pose and illumination variations.},
	keywords = {adaptive, adaptive-velocity, appearance, extra-personal, Filtering, filters;, image, intra-personal, model;, MOTION, particle, processing;, recognition;, sequence;, sequences;, series, signal, spaces;, theory;, TIME, tracking;, video, visual},
	doi = {10.1109/ICME.2003.1221625},
	author = {Zhou,Shaohua and Chellapa, Rama and Moghaddam, B.}
}
@conference {12721,
	title = {An appearance based approach for human and object tracking},
	booktitle = {Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on},
	volume = {2},
	year = {2003},
	month = {2003/09//},
	pages = {II - 85-8 vol.3 - II - 85-8 vol.3},
	abstract = {A system for tracking humans and detecting human-object interactions in indoor environments is described. A combination of correlogram and histogram information is used to model object and human color distributions. Humans and objects are detected using a background subtraction algorithm. The models are built on the fly and used to track them on a frame by frame basis. The system is able to detect when people merge into groups and segment them during occlusion. Identities are preserved during the sequence, even if a person enters and leaves the scene. The system is also able to detect when a person deposits or removes an object from the scene. In the first case the models are used to track the object retroactively in time. In the second case the objects are tracked for the rest of the sequence. Experimental results using indoor video sequences are presented.},
	keywords = {algorithm;, analysis;, background, basis;, by, Color, colour, correlogram, detection;, distributions;, frame, histogram, human, image, information;, object, processing;, segmentation;, sequences;, signal, subtraction, tracking;, video},
	doi = {10.1109/ICIP.2003.1246622},
	author = {Capellades,M. B and David Doermann and DeMenthon,D. and Chellapa, Rama}
}
@conference {17812,
	title = {The CPR model for summarizing video},
	booktitle = {Proceedings of the 1st ACM international workshop on Multimedia databases},
	series = {MMDB {\textquoteright}03},
	year = {2003},
	month = {2003///},
	pages = {2 - 9},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Most past work on video summarization has been based on selecting key frames from videos. We propose a model of video summarization based on three important parameters: Priority (of frames), Continuity (of the summary), and non-Repetition (of the summary). In short, a summary must include high priority frames, must be continuous and non-repetitive. An optimal summary is one that maximizes an objective function based on these three parameters. We develop formal definitions of all these concepts and provide algorithms to find optimal summaries. We briefly report on the performance of these algorithms.},
	keywords = {multimedia, Summarization, video},
	isbn = {1-58113-726-5},
	doi = {10.1145/951676.951679},
	url = {http://doi.acm.org/10.1145/951676.951679},
	author = {Fayzullin,M. and V.S. Subrahmanian and Picariello, A. and Sapino,M. L}
}
@article {18193,
	title = {Data hiding in image and video .I. Fundamental issues and solutions},
	journal = {Image Processing, IEEE Transactions on},
	volume = {12},
	year = {2003},
	month = {2003/06//},
	pages = {685 - 695},
	abstract = {We address a number of fundamental issues of data hiding in image and video and propose general solutions to them. We begin with a review of two major types of embedding, based on which we propose a new multilevel embedding framework to allow the amount of extractable data to be adaptive according to the actual noise condition. We then study the issues of hiding multiple bits through a comparison of various modulation and multiplexing techniques. Finally, the nonstationary nature of visual signals leads to highly uneven distribution of embedding capacity and causes difficulty in data hiding. We propose an adaptive solution switching between using constant embedding rate with shuffling and using variable embedding rate with embedded control bits. We verify the effectiveness of our proposed solutions through analysis and simulation.},
	keywords = {adaptive, analysis;, bits;, colour, condition;, constant, CONTROL, data, embedded, EMBEDDING, embedding;, encapsulation;, extractable, hiding;, image, Modulation, modulation;, multilevel, multiplexing, multiplexing;, NOISE, nonstationary, processing;, rate;, reviews;, shuffling;, signal, signals;, simulation;, solution;, techniques;, variable, video, visual},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2003.810588},
	author = {M. Wu and Liu,Bede}
}
@article {18194,
	title = {Data hiding in image and video .II. Designs and applications},
	journal = {Image Processing, IEEE Transactions on},
	volume = {12},
	year = {2003},
	month = {2003/06//},
	pages = {696 - 705},
	abstract = {For pt. I see ibid., vol.12, no.6, p.685-95 (2003). This paper applies the solutions to the fundamental issues addressed in Part I to specific design problems of embedding data in image and video. We apply multilevel embedding to allow the amount of embedded information that can be reliably extracted to be adaptive with respect to the actual noise conditions. When extending the multilevel embedding to video, we propose strategies for handling uneven embedding capacity from region to region within a frame as well as from frame to frame. We also embed control information to facilitate the accurate extraction of the user data payload and to combat such distortions as frame jitter. The proposed algorithm can be used for a variety of applications such as copy control, access control, robust annotation, and content-based authentication.},
	keywords = {access, annotation;, authentication;, capacity;, conditions;, content-based, CONTROL, control;, copy, data, distortions;, EMBEDDING, embedding;, encapsulation;, extraction;, frame, hiding;, image, information;, jitter;, message, multilevel, NOISE, noise;, payload, processing;, robust, signal, uneven, user, video},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2003.810589},
	author = {M. Wu and Yu,H. and Liu,Bede}
}
@conference {13245,
	title = {Scalable image-based multi-camera visual surveillance system},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {205 - 212},
	abstract = {We describe the design of a scalable and wide coverage visual surveillance system. Scalability (the ability to add and remove cameras easily during system operation with minimal overhead and system degradation) is achieved by utilizing only image-based information for camera control. We show that when a pan-tilt-zoom camera pans and tilts, a given image point moves in a circular and a linear trajectory, respectively. We create a scene model using a plan view of the scene. The scene model makes it easy for us to handle occlusion prediction and schedule video acquisition tasks subject to visibility constraints. We describe a maximum weight matching algorithm to assign cameras to tasks that meet the visibility constraints. The system is illustrated both through simulations and real video from a 6-camera configuration.},
	keywords = {ACQUISITION, algorithm;, camera;, constraints;, feature, hidden, image-based, MATCHING, maximum, multi-camera, occlusion, pan-tilt-zoom, PLAN, prediction;, processing;, removal;, scalable, scheduling;, signal, Surveillance, surveillance;, system;, task, video, view;, visibility, visual, weight},
	doi = {10.1109/AVSS.2003.1217923},
	author = {Lim,Ser-Nam and Davis, Larry S. and Elgammal,A.}
}
@conference {12725,
	title = {Shape and motion driven particle filtering for human body tracking},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/07//},
	pages = {III - 61-4 vol.3 - III - 61-4 vol.3},
	abstract = {In this paper, we propose a method to recover 3D human body motion from a video acquired by a single static camera. In order to estimate the complex state distribution of a human body, we adopt the particle filtering framework. We present the human body using several layers of representation and compose the whole body step by step. In this way, more effective particles are generated and ineffective particles are removed as we process each layer. In order to deal with the rotational motion, the frequency of rotation is obtained using a preprocessing operation. In the preprocessing step, the variance of the motion field at each image is computed, and the frequency of rotation is estimated. The estimated frequency is used for the state update in the algorithm. We successfully track the movement of figure skaters in TV broadcast image sequence, and recover the 3D shape and motion of the skater.},
	keywords = {3D, body, broadcast, camera;, cameras;, estimation;, Filtering, framework;, human, image, MOTION, motion;, particle, processing;, rotational, sequence;, sequences;, signal, single, static, theory;, tracking;, TV, video},
	doi = {10.1109/ICME.2003.1221248},
	author = {Yamamoto, T. and Chellapa, Rama}
}
@conference {12732,
	title = {Simultaneous tracking and recognition of human faces from video},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 225-8 vol.3 - III - 225-8 vol.3},
	abstract = {The paper investigates the interaction between tracking and recognition of human faces from video under a framework proposed earlier (Shaohua Zhou et al., Proc. 5th Int. Conf. on Face and Gesture Recog., 2002; Shaohua Zhou and Chellappa, R., Proc. European Conf. on Computer Vision, 2002), where a time series model is used to resolve the uncertainties in both tracking and recognition. However, our earlier efforts employed only a simple likelihood measurement in the form of a Laplacian density to deal with appearance changes between frames and between the observation and gallery images, yielding poor accuracies in both tracking and recognition when confronted by pose and illumination variations. The interaction between tracking and recognition was not well understood. We address the interdependence between tracking and recognition using a series of experiments and quantify the interacting nature of tracking and recognition.},
	keywords = {appearance, changes;, density;, Face, human, illumination, Laplacian, model;, optical, pose, processing;, recognition;, series, series;, signal, TIME, tracking;, variations;, video, video;},
	doi = {10.1109/ICASSP.2003.1199148},
	author = {Zhou,Shaohua and Chellapa, Rama}
}
@conference {12733,
	title = {Statistical shape theory for activity modeling},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 493-6 vol.3 - III - 493-6 vol.3},
	abstract = {Monitoring activities in a certain region from video data is an important surveillance problem. The goal is to learn the pattern of normal activities and detect unusual ones by identifying activities that deviate appreciably from the typical ones. We propose an approach using statistical shape theory based on the shape model of D.G. Kendall et al. (see "Shape and Shape Theory", John Wiley and Sons, 1999). In a low resolution video, each moving object is best represented as a moving point mass or particle. In this case, an activity can be defined by the interactions of all or some of these moving particles over time. We model this configuration of the particles by a polygonal shape formed from the locations of the points in a frame and the activity by the deformation of the polygons in time. These parameters are learned for each typical activity. Given a test video sequence, an activity is classified as abnormal if the probability for the sequence (represented by the mean shape and the dynamics of the deviations), given the model, is below a certain threshold The approach gives very encouraging results in surveillance applications using a single camera and is able to identify various kinds of abnormal behavior.},
	keywords = {abnormal, activities, activity, analysis;, behavior;, classification;, data;, image, mass;, matching;, modeling;, monitoring;, moving, normal, particle;, pattern, pattern;, point, polygonal, probability;, problem;, processing;, sequence;, sequences;, SHAPE, shape;, signal, statistical, Surveillance, surveillance;, theory;, video},
	doi = {10.1109/ICASSP.2003.1199519},
	author = {Vaswani, N. and Chowdhury, A.R. and Chellapa, Rama}
}
@conference {12727,
	title = {Video based rendering of planar dynamic scenes},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {1},
	year = {2003},
	month = {2003/07//},
	pages = {I - 477-80 vol.1 - I - 477-80 vol.1},
	abstract = {In this paper, we propose a method to synthesize arbitrary views of a planar scene from a monocular video sequence of it. The 3-D direction of motion of the object is robustly estimated from the video sequence. Given this direction any other view of the object can be synthesized through a perspective projection approach, under assumptions of planarity. If the distance of the object from the camera is large, a planar approximation is reasonable even for non-planar scenes. Such a method has many important applications, one of them being gait recognition where a side view of the person is required. Our method can be used to synthesize the side-view of the person in case he/she does not present a side view to the camera. Since the planarity assumption is often an approximation, the effects of non-planarity can lead to inaccuracies in rendering and needs to be corrected for. Regions where this happens are examined and a simple technique based on weak perspective approximation is proposed to offset rendering inaccuracies. Examples of synthesized views using our method and performance evaluation are presented.},
	keywords = {(computer, 3D, analysis;, approximation;, based, camera;, cameras;, direction;, dynamic, graphics);, image, monocular, MOTION, perspective, planar, processing;, rendering, rendering;, scenes;, sequence;, sequences;, signal, video, weak},
	doi = {10.1109/ICME.2003.1220958},
	author = {Kale, A. and Chowdhury, A.K.R. and Chellapa, Rama}
}
@conference {12735,
	title = {Video synthesis of arbitrary views for approximately planar scenes},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 497-500 vol.3 - III - 497-500 vol.3},
	abstract = {In this paper, we propose a method to synthesize arbitrary views of a planar scene, given a monocular video sequence. The method is based on the availability of knowledge of the angle between the original and synthesized views. Such a method has many important applications, one of them being gait recognition. Gait recognition algorithms rely on the availability of an approximate side-view of the person. From a realistic viewpoint, such an assumption is impractical in surveillance applications and it is of interest to develop methods to synthesize a side view of the person, given an arbitrary view. For large distances from the camera, a planar approximation for the individual can be assumed. In this paper, we propose a perspective projection approach for recovering the direction of motion of the person purely from the video data, followed by synthesis of a new video sequence at a different angle. The algorithm works purely in the image and video domain, though 3D structure plays an implicit role in its theoretical justification. Examples of synthesized views using our method and performance evaluation are presented.},
	keywords = {(access, 3D, applications;, approach;, approximately, approximation;, arbitrary, Biometrics, control);, data;, direction, estimation;, evaluation;, Gait, image, monocular, MOTION, performance, perspective, planar, processing;, projection, recognition;, recovery;, scenes;, sequence;, sequences;, side, signal, structure;, Surveillance, surveillance;, synthesis;, synthesized, video, view, views;},
	doi = {10.1109/ICASSP.2003.1199520},
	author = {Chowdhury, A.K.R. and Kale, A. and Chellapa, Rama}
}
@conference {12765,
	title = {3D face reconstruction from video using a generic model},
	booktitle = {Multimedia and Expo, 2002. ICME {\textquoteright}02. Proceedings. 2002 IEEE International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {449 - 452 vol.1 - 449 - 452 vol.1},
	abstract = {Reconstructing a 3D model of a human face from a video sequence is an important problem in computer vision, with applications to recognition, surveillance, multimedia etc. However, the quality of 3D reconstructions using structure from motion (SfM) algorithms is often not satisfactory. One common method of overcoming this problem is to use a generic model of a face. Existing work using this approach initializes the reconstruction algorithm with this generic model. The problem with this approach is that the algorithm can converge to a solution very close to this initial value, resulting in a reconstruction which resembles the generic model rather than the particular face in the video which needs to be modeled. We propose a method of 3D reconstruction of a human face from video in which the 3D reconstruction algorithm and the generic model are handled separately. A 3D estimate is obtained purely from the video sequence using SfM algorithms without use of the generic model. The final 3D model is obtained after combining the SfM estimate and the generic model using an energy function that corrects for the errors in the estimate by comparing local regions in the two models. The optimization is done using a Markov chain Monte Carlo (MCMC) sampling strategy. The main advantage of our algorithm over others is that it is able to retain the specific features of the face in the video sequence even when these features are different from those of the generic model. The evolution of the 3D model through the various stages of the algorithm is presented.},
	keywords = {3D, algorithm;, algorithms;, analysis;, Carlo, chain, Computer, Face, from, function;, generic, human, image, Markov, MCMC, methods;, model;, Monte, MOTION, optimisation;, OPTIMIZATION, processes;, processing;, recognition;, reconstruction, reconstruction;, sampling;, sequence;, sequences;, SfM, signal, structure, surveillance;, video, vision;},
	doi = {10.1109/ICME.2002.1035815},
	author = {Chowdhury, A.R. and Chellapa, Rama and Krishnamurthy, S. and Vo, T.}
}
@conference {12758,
	title = {Bayesian structure from motion using inertial information},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {III-425 - III-428 vol.3 - III-425 - III-428 vol.3},
	abstract = {A novel approach to Bayesian structure from motion (SfM) using inertial information and sequential importance sampling (SIS) is presented. The inertial information is obtained from camera-mounted inertial sensors and is used in the Bayesian SfM approach as prior knowledge of the camera motion in the sampling algorithm. Experimental results using both synthetic and real images show that, when inertial information is used, more accurate results can be obtained or the same estimation accuracy can be obtained at a lower cost.},
	keywords = {3D, analysis;, Bayes, Bayesian, camera, estimation;, image, images;, importance, inertial, information;, methods;, MOTION, motion;, parameter, processing;, real, reconstruction;, sampling;, scene, sensors;, sequence;, sequences;, sequential, signal, structure-from-motion;, synthetic, systems;, video},
	doi = {10.1109/ICIP.2002.1038996},
	author = {Qian,Gang and Chellapa, Rama and Qinfen Zheng}
}
@conference {12749,
	title = {Face recognition from video: a CONDENSATION approach},
	booktitle = {Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE International Conference on},
	year = {2002},
	month = {2002/05//},
	pages = {221 - 226},
	abstract = {The aim of this work is to investigate how to exploit the temporal information in a video sequence for the task of face recognition. Following the approach in (Li and Chellappa, 2000), we propose a probabilistic model parameterized by a tracking state vector and a recognizing identity variable, simultaneously characterizing the kinematics and identity of humans. We then invoke a CONDENSATION (Isard and Blake, 1996) approach to provide a numerical solution to the model. Once the joint posterior distribution of the state vector and the identity variable is estimated, we marginalize it over the state vector to yield a robust estimate of the posterior distribution of the identity variable. Due to the propagation of identity and dynamics, a degeneracy in the posterior distribution of the identity variable is achieved to give improved recognition. This evolving behavior is characterized using changes in entropy. The effectiveness of this approach is illustrated using experimental results on low-resolution video data.},
	keywords = {algorithm;experimental, approach;Sequential, CONDENSATION, data;probabilistic, distribution;kinematics;low-resolution, importance, information;tracking, model;state, posterior, recognition;image, recognition;joint, resolution;image, results;face, sampling, sampling;probability;, sequence;face, sequences;importance, state, vector;temporal, vector;video, video},
	doi = {10.1109/AFGR.2002.1004158},
	author = {Zhou,Shaohua and Krueger, V. and Chellapa, Rama}
}
@article {12752,
	title = {A generic approach to simultaneous tracking and verification in video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {11},
	year = {2002},
	month = {2002/05//},
	pages = {530 - 544},
	abstract = {A generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H<sub>1</sub> and H0, we first estimate posterior probabilities P(H<sub>0</sub>|Z) and P(H<sub>1</sub>|Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.},
	keywords = {approach;, Carlo, configuration;, correspondence, data;, density, density;, estimated, estimation;, evaluation;, extraction;, Face, facial, feature, generic, human, hypothesis, image, measurement, methods;, Monte, object, performance, posterior, probability, probability;, problem;, processing;, propagation;, recognition;, road, sequence, sequences;, sequential, signal, space;, stabilization;, state, synthetic, temporal, testing;, tracking;, vector;, vehicle, vehicles;, verification;, video, visual},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2002.1006400},
	author = {Li,Baoxin and Chellapa, Rama}
}
@conference {12746,
	title = {A hierarchical approach for obtaining structure from two-frame optical flow},
	booktitle = {Motion and Video Computing, 2002. Proceedings. Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {214 - 219},
	abstract = {A hierarchical iterative algorithm is proposed for extracting structure from two-frame optical flow. The algorithm exploits two facts: one is that in many applications, such as face and gesture recognition, the depth variation of the visible surface of an object in a scene is small compared to the distance between the optical center and the object; the other is that the time aliasing problem is alleviated at the coarse level for any two-frame optical flow estimate so that the estimate tends to be more accurate. A hierarchical representation for the relationship between the optical flow, depth, and the motion parameters is derived, and the resulting non-linear system is iteratively solved through two linear subsystems. At the coarsest level, the surface of the object tends to be flat, so that the inverse depth tends to be a constant, which is used as the initial depth map. Inverse depth and motion parameters are estimated by the two linear subsystems at each level and the results are propagated to finer levels. Error analysis and experiments using both computer-rendered images and real images demonstrate the correctness and effectiveness of our algorithm.},
	keywords = {algorithm;, aliasing;, analysis;, computer-rendered, depth, depth;, error, estimation;, extraction;, Face, feature, flow;, gesture, hierarchical, image, images;, inverse, iterative, methods;, MOTION, nonlinear, optical, parameter, processing;, real, recognition;, sequences;, signal, structure-from-motion;, system;, systems;, TIME, two-frame, variation;, video},
	doi = {10.1109/MOTION.2002.1182239},
	author = {Liu,Haiying and Chellapa, Rama and Rosenfeld, A.}
}
@conference {13623,
	title = {Performance evaluation of object detection algorithms},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {965 - 969 vol.3 - 965 - 969 vol.3},
	abstract = {The continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. In this paper a set of seven metrics are proposed for quantifying different aspects of a detection algorithm{\textquoteright}s performance. The strengths and weaknesses of these metrics are described. They are implemented in the Video Performance Evaluation Resource (ViPER) system and will be used to evaluate algorithms for detecting text, faces, moving people and vehicles. Results for running two previous text-detection algorithms on a common data set are presented.},
	keywords = {algorithms;, common, data, DETECTION, detection;, Evaluation, evaluation;, image, object, performance, recognition;, resource, set;, system;, text-detection, video},
	doi = {10.1109/ICPR.2002.1048198},
	author = {Mariano,V.Y. and Min,Junghye and Park,Jin-Hyeong and Kasturi,R. and Mihalcik,D. and Huiping Li and David Doermann and Drayer,T.}
}
@article {17815,
	title = {Presentation planning for distributed VoD systems},
	journal = {Knowledge and Data Engineering, IEEE Transactions on},
	volume = {14},
	year = {2002},
	month = {2002/10//sep},
	pages = {1059 - 1077},
	abstract = {A distributed video-on-demand (VoD) system is one where a collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in distributed VoD systems, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present different types of presentation plans that a local server can construct in order to satisfy a customer request. Informally speaking, a presentation plan is a temporally synchronized sequence of steps that the local server must perform in order to present the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, while keeping within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, in order to evaluate the quality of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer and minimizing access bandwidth which, informally speaking, specifies how much network/disk bandwidth is used. We develop algorithms to compute three different optimal presentation plans that work at a block level, or at a segment level, or with a hybrid mix of the two, and compare their performance through simulation experiments. We have also mathematically proven effects of increased buffer or bandwidth and data replications for presentation plans which had previously been verified experimentally in the literature.},
	keywords = {Computer, computing;, databases;, demand;, distributed, local, multimedia, network;, on, optimal, plan;, plans;, presentation, presentation;, server;, servers;, video, video-on-demand;, VoD;},
	isbn = {1041-4347},
	doi = {10.1109/TKDE.2002.1033774},
	author = {Hwang,Eenjun and Prabhakaran,B. and V.S. Subrahmanian}
}
@conference {12766,
	title = {Probabilistic recognition of human faces from video},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {I-41 - I-44 vol.1 - I-41 - I-44 vol.1},
	abstract = {Most present face recognition approaches recognize faces based on still images. We present a novel approach to recognize faces in video. In that scenario, the face gallery may consist of still images or may be derived from a videos. For evidence integration we use classical Bayesian propagation over time and compute the posterior distribution using sequential importance sampling. The probabilistic approach allows us to handle uncertainties in a systematic manner. Experimental results using videos collected by NIST/USF and CMU illustrate the effectiveness of this approach in both still-to-video and video-to-video scenarios with appropriate model choices.},
	keywords = {Bayes, Bayesian, CMU;, distribution;, Face, faces;, gallery;, handling;, human, image, images;, importance, likelihood;, methods;, NIST/USF;, observation, posterior, probabilistic, probability;, processing;, propagation;, recognition;, sampling;, sequential, signal, still, Still-to-video, Uncertainty, video, Video-to-video},
	doi = {10.1109/ICIP.2002.1037954},
	author = {Chellapa, Rama and Kruger, V. and Zhou,Shaohua}
}
@conference {12747,
	title = {Wide baseline image registration using prior information},
	booktitle = {Multimedia Signal Processing, 2002 IEEE Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {37 - 40},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles in a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, 3D model alignment, creation of panoramic views etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching 2D shapes of the different features of the face. A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellations of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, alignment;, angles;, baseline, Computer, configuration;, constellation;, correspondence, creation;, doubly, error, extraction;, Face, feature, global, holistic, image, images;, matching;, matrix;, model, models;, normalization, panoramic, probability;, procedure;, processes;, processing;, registration;, robust, sequences;, SHAPE, signal, Sinkhorn, spatial, statistics;, stereo;, Stochastic, video, view, viewing, vision;, wide},
	doi = {10.1109/MMSP.2002.1203242},
	author = {Chowdhury, AM and Chellapa, Rama and Keaton, T.}
}
@article {18206,
	title = {Dynamic resource allocation via video content and short-term traffic statistics},
	journal = {Multimedia, IEEE Transactions on},
	volume = {3},
	year = {2001},
	month = {2001/06//},
	pages = {186 - 199},
	abstract = {The reliable and efficient transmission of high-quality variable bit rate (VBR) video through the Internet generally requires network resources be allocated in a dynamic fashion. This includes the determination of when to renegotiate for network resources, as well as how much to request at a given time. The accuracy of any resource request method depends critically on its prediction of future traffic patterns. Such a prediction can be performed using the content and traffic information of short video segments. This paper presents a systematic approach to select the best features for prediction, indicating that while content is important in predicting the bandwidth of a video hit stream, the use of both content and available short-term bandwidth statistics can yield significant improvements. A new framework for traffic prediction is proposed in this paper; experimental results show a smaller mean-square resource prediction error and higher overall link utilization},
	keywords = {allocation;link, allocation;multimedia, allocation;variable, bit, codes;, content;bandwidth, error;short, Internet;dynamic, patterns;variable, prediction, rate, resource, segments;short-term, statistics;traffic, systems;resource, traffic, utilization;mean-square, video, video;video},
	isbn = {1520-9210},
	doi = {10.1109/6046.923818},
	author = {M. Wu and Joyce,R.A. and Wong,Hau-San and Guan,Long and Kung,Sun-Yuan}
}
@conference {14188,
	title = {A spherical eye from multiple cameras (makes better models of the world)},
	booktitle = {Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001},
	volume = {1},
	year = {2001},
	month = {2001///},
	pages = {I-576- I-583 vol.1 - I-576- I-583 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The paper describes an imaging system that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system{\textquoteright}s own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. We provide algorithms for the calibration of the system and 3D motion estimation. The calibration is based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients.},
	keywords = {3D motion estimation, Calibration, camera network, CAMERAS, Computer vision, egomotion recovery, geometric configuration, geometric constraint, image gradients, image sampling, imaging system, Laboratories, Layout, Motion estimation, multiple cameras, Pixel, Robot vision systems, SHAPE, shape models, Space technology, spherical eye, system calibration, video, video cameras, video signal processing, visual sphere sampling},
	isbn = {0-7695-1272-0},
	doi = {10.1109/CVPR.2001.990525},
	author = {Baker, P. and Ferm{\"u}ller, Cornelia and Aloimonos, J. and Pless, R.}
}
@conference {13583,
	title = {Live multimedia adaptation through wireless hybrid networks},
	booktitle = {Multimedia and Expo, 2000. ICME 2000. 2000 IEEE International Conference on},
	volume = {3},
	year = {2000},
	month = {2000///},
	pages = {1697 -1700 vol.3 - 1697 -1700 vol.3},
	abstract = {We present new techniques to intelligently adapt and combine multimedia presentations in real-time, mobile service environments. We present the techniques necessary to perform mobile multimedia processing for multiple video streams with ldquo;value-adding rdquo; information. The adaptation uses video analysis, content-recognition and automated annotation to provide scalable and interactive presentations over hybrid networks to mobile terminals. As a concrete case, we present a mobile surveillance service called Princess, which has several video sources and supports control information, terminal adaptation and end-to-end service},
	keywords = {adaptation;mobile, adaptation;value-adding, analysis;wireless, annotation;content-recognition;end-to-end, communication;multimedia, communication;real-time, hybrid, information;video, LAN;, multimedia, networks;mobile, Princess;automated, processing;mobile, service;live, service;mobile, streams;real-time, Surveillance, system;terminal, systems;surveillance;wireless, terminals;multiple, video},
	doi = {10.1109/ICME.2000.871098},
	author = {Koivisto,A. and Pietkainen,P. and Sauvola,J. and David Doermann}
}
@conference {14881,
	title = {Segmenting independently moving, noisy points},
	booktitle = {Motion of Non-Rigid and Articulated Objects, 1994., Proceedings of the 1994 IEEE Workshop on},
	year = {1994},
	month = {1994/11//},
	pages = {96 - 103},
	abstract = {There has been much work on using point features tracked through a video sequence to determine structure and motion. In many situations, to use this work, we must first isolate subsets of points that share a common motion. This is hard because we must distinguish between independent motions and apparent deviations from a single motion due to noise. We propose several methods of searching for point-sets with consistent 3D motions. We analyze the potential sensitivity of each method for detecting independent motions, and experiment with each method on a real image sequence},
	keywords = {3D, common, consistent, estimation;, features;, image, independently, linear, MOTION, motion;, moving, noisy, point, points;, programming;, real, segmentation;, sequence;, sequences;, video},
	doi = {10.1109/MNRAO.1994.346249},
	author = {Jacobs, David W. and Chennubhotla,C.}
}
