@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 {17911,
	title = {Salient Clustering for View-dependent Multiresolution Rendering},
	booktitle = {Computer Graphics and Image Processing (SIBGRAPI), 2009 XXII Brazilian Symposium on},
	year = {2009},
	month = {2009/10//},
	pages = {56 - 63},
	abstract = {Perceptual information is quickly gaining importance in mesh representation, analysis and rendering. User studies, eye tracking and other techniques are able to provide ever more useful insights for many user-centric systems, which form the bulk of computer graphics applications. In this work we build upon the concept of Mesh Saliency - an automatic measure of visual importance for triangle meshes based on models of low-level human visual attention - applying it to the problem of mesh segmentation and view-dependent rendering. We introduce a technique for segmentation that partitions an object into a set of face clusters, each encompassing a group of locally interesting features; Mesh Saliency is incorporated in a propagative mesh clustering framework, guiding cluster seed selection and triangle propagation costs and leading to a convergence of face clusters around perceptually important features. We compare our technique with different fully automatic segmentation algorithms, showing that it provides similar or better segmentation without the need for user input. We illustrate application of our clustering results through a saliency-guided view-dependent rendering system, achieving significant frame rate increases with little loss of visual detail.},
	keywords = {(computer, algorithms;cluster, analysis;mesh, attention;mesh, AUTOMATIC, centred, clustering, clustering;rendering, clustering;user-centric, clusters;low-level, dependent, design;, framework;salient, graphics);user, graphics;face, human, information;propagative, mesh, multiresolution, rendering;image, representation;mesh, resolution;image, saliency;mesh, seed, segmentation, segmentation;pattern, segmentation;perceptual, selection;computer, system;view, visual},
	doi = {10.1109/SIBGRAPI.2009.34},
	author = {Barni,R. and Comba,J. and Varshney, Amitabh}
}
@article {16060,
	title = {Visual-Analytics Evaluation},
	journal = {Computer Graphics and Applications, IEEE},
	volume = {29},
	year = {2009},
	month = {2009/06//may},
	pages = {16 - 17},
	abstract = {Visual analytics (VA) is the science of analytical reasoning facilitated by interactive visual interfaces. Assessing VA technology{\textquoteright}s effectiveness is challenging because VA tools combine several disparate components, both low and high level, integrated in complex interactive systems used by analysts, emergency responders, and others. These components include analytical reasoning, visual representations, computer-human interaction techniques, data representations and transformations, collaboration tools, and especially tools for communicating the results of their use. VA tool users{\textquoteright} activities can be exploratory and can take place over days, weeks, or months. Users might not follow a predefined or even linear work flow. They might work alone or in groups. To understand these complex behaviors, an evaluation can target the component level, the system level, or the work environment level, and requires realistic data and tasks. Traditional evaluation metrics such as task completion time, number of errors, or recall and precision are insufficient to quantify the utility of VA tools, and new research is needed to improve our VA evaluation methodology.},
	keywords = {analytic, analytics, evaluation;cognition;data, generation;user, interactive, interfaces;synthetic-data-set, reasoning;visual, systems;, tools;visual, visual, visualisation;interactive},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2009.56},
	author = {Plaisant, Catherine and Grinstein,G. and Scholtz,J.}
}
@conference {13146,
	title = {Bilattice-based Logical Reasoning for Human Detection},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 8},
	abstract = {The capacity to robustly detect humans in video is a critical component of automated visual surveillance systems. This paper describes a bilattice based logical reasoning approach that exploits contextual information and knowledge about interactions between humans, and augments it with the output of different low level detectors for human detection. Detections from low level parts-based detectors are treated as logical facts and used to reason explicitly about the presence or absence of humans in the scene. Positive and negative information from different sources, as well as uncertainties from detections and logical rules, are integrated within the bilattice framework. This approach also generates proofs or justifications for each hypothesis it proposes. These justifications (or lack thereof) are further employed by the system to explain and validate, or reject potential hypotheses. This allows the system to explicitly reason about complex interactions between humans and handle occlusions. These proofs are also available to the end user as an explanation of why the system thinks a particular hypothesis is actually a human. We employ a boosted cascade of gradient histograms based detector to detect individual body parts. We have applied this framework to analyze the presence of humans in static images from different datasets.},
	keywords = {automated, detection;parts-based, detectors;static, histograms;human, images;formal, interactions;gradient, logic;image, logical, mechanisms;surveillance;video, processing;, reasoning;complex, recognition;inference, signal, Surveillance, systems;bilattice-based, visual},
	doi = {10.1109/CVPR.2007.383133},
	author = {Shet,V. D and Neumann, J. and Ramesh,V. and Davis, Larry S.}
}
@conference {13991,
	title = {Microphone Arrays as Generalized Cameras for Integrated Audio Visual Processing},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 8},
	abstract = {Combinations of microphones and cameras allow the joint audio visual sensing of a scene. Such arrangements of sensors are common in biological organisms and in applications such as meeting recording and surveillance where both modalities are necessary to provide scene understanding. Microphone arrays provide geometrical information on the source location, and allow the sound sources in the scene to be separated and the noise suppressed, while cameras allow the scene geometry and the location and motion of people and other objects to be estimated. In most previous work the fusion of the audio-visual information occurs at a relatively late stage. In contrast, we take the viewpoint that both cameras and microphone arrays are geometry sensors, and treat the microphone arrays as generalized cameras. We employ computer-vision inspired algorithms to treat the combined system of arrays and cameras. In particular, we consider the geometry introduced by a general microphone array and spherical microphone arrays. The latter show a geometry that is very close to central projection cameras, and we show how standard vision based calibration algorithms can be profitably applied to them. Experiments are presented that demonstrate the usefulness of the considered approach.},
	keywords = {algorithms;generalized, arrays;scene, arrays;sensor, audio, audio-visual, cameras;geometrical, fusion;, fusion;computer-vision, geometry;sound, information, information;geometry, inspired, location;acoustic, processing;array, processing;audio-visual, processing;microphone, sensors;integrated, signal, sources;source, systems;cameras;computer, vision;geometry;microphone, visual},
	doi = {10.1109/CVPR.2007.383345},
	author = {O{\textquoteright}Donovan,A. and Duraiswami, Ramani and Neumann, J.}
}
@conference {14498,
	title = {D-Dupe: An Interactive Tool for Entity Resolution in Social Networks},
	booktitle = {Visual Analytics Science And Technology, 2006 IEEE Symposium On},
	year = {2006},
	month = {2006/11/31/2},
	pages = {43 - 50},
	abstract = {Visualizing and analyzing social networks is a challenging problem that has been receiving growing attention. An important first step, before analysis can begin, is ensuring that the data is accurate. A common data quality problem is that the data may inadvertently contain several distinct references to the same underlying entity; the process of reconciling these references is called entity-resolution. D-Dupe is an interactive tool that combines data mining algorithms for entity resolution with a task-specific network visualization. Users cope with complexity of cleaning large networks by focusing on a small subnetwork containing a potential duplicate pair. The subnetwork highlights relationships in the social network, making the common relationships easy to visually identify. D-Dupe users resolve ambiguities either by merging nodes or by marking them distinct. The entity resolution process is iterative: as pairs of nodes are resolved, additional duplicates may be revealed; therefore, resolution decisions are often chained together. We give examples of how users can flexibly apply sequences of actions to produce a high quality entity resolution result. We illustrate and evaluate the benefits of D-Dupe on three bibliographic collections. Two of the datasets had already been cleaned, and therefore should not have contained duplicates; despite this fact, many duplicates were rapidly identified using D-Dupe{\textquoteright}s unique combination of entity resolution algorithms within a task-specific visual interface},
	keywords = {algorithm;data, analysis;social, computing;user, D-Dupe, interactive, interface;data, interfaces;, mining, mining;interactive, network, problem;entity, QUALITY, resolution;entity-resolution;social, sciences, systems;social, tool;data, visual, visualization;task-specific},
	doi = {10.1109/VAST.2006.261429},
	author = {Bilgic,M. and Licamele,L. and Getoor, Lise and Shneiderman, Ben}
}
@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 {13186,
	title = {Fast multiple object tracking via a hierarchical particle filter},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {1},
	year = {2005},
	month = {2005/10//},
	pages = {212 - 219 Vol. 1 - 212 - 219 Vol. 1},
	abstract = {A very efficient and robust visual object tracking algorithm based on the particle filter is presented. The method characterizes the tracked objects using color and edge orientation histogram features. While the use of more features and samples can improve the robustness, the computational load required by the particle filter increases. To accelerate the algorithm while retaining robustness we adopt several enhancements in the algorithm. The first is the use of integral images for efficiently computing the color features and edge orientation histograms, which allows a large amount of particles and a better description of the targets. Next, the observation likelihood based on multiple features is computed in a coarse-to-fine manner, which allows the computation to quickly focus on the more promising regions. Quasi-random sampling of the particles allows the filter to achieve a higher convergence rate. The resulting tracking algorithm maintains multiple hypotheses and offers robustness against clutter or short period occlusions. Experimental results demonstrate the efficiency and effectiveness of the algorithm for single and multiple object tracking.},
	keywords = {(numerical, algorithm;, analysis;, Color, colour, Computer, Convergence, detection;, edge, fast, filter;, Filtering, hierarchical, histogram;, image, images;, integral, likelihood;, methods);, methods;, multiple, numerical, object, observation, of, orientation, particle, processes;, quasirandom, random, sampling;, tracking, tracking;, vision;, visual},
	doi = {10.1109/ICCV.2005.95},
	author = {Yang,Changjiang and Duraiswami, Ramani and Davis, Larry S.}
}
@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 {14845,
	title = {Using the inner-distance for classification of articulated shapes},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {2},
	year = {2005},
	month = {2005/06//},
	pages = {719 - 726 vol. 2 - 719 - 726 vol. 2},
	abstract = {We propose using the inner-distance between landmark points to build shape descriptors. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that the inner-distance is articulation insensitive and more effective at capturing complex shapes with part structures than Euclidean distance. To demonstrate this idea, it is used to build a new shape descriptor based on shape contexts. After that, we design a dynamic programming based method for shape matching and comparison. We have tested our approach on a variety of shape databases including an articulated shape dataset, MPEG7 CE-Shape-1, Kimia silhouettes, a Swedish leaf database and a human motion silhouette dataset. In all the experiments, our method demonstrates effective performance compared with other algorithms.},
	keywords = {articulated, CE-Shape-1, classification;, database;, databases;, dataset;, descriptor;, dynamic, human, image, inner-distance;, Kimia, landmark, leaf, matching;, MOTION, MPEG7, points;, programming;, SHAPE, silhouette, silhouette;, Swedish, visual},
	doi = {10.1109/CVPR.2005.362},
	author = {Ling,H. and Jacobs, David W.}
}
@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 {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 {12685,
	title = {Facial similarity across age, disguise, illumination and pose},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/10//},
	pages = {1999 - 2002 Vol. 3 - 1999 - 2002 Vol. 3},
	abstract = {Illumination, pose variations, disguises, aging effects and expression variations are some of the key factors that affect the performance of face recognition systems. Face recognition systems have always been studied from a recognition perspective. Our emphasis is on deriving a measure of similarity between faces. The similarity measure provides insights into the role each of the above mentioned variations play in affecting the performance of face recognition systems. In the process of computing the similarity measure between faces, we suggest a framework to compensate for pose variations and introduce the notion of {\textquoteright}half-faces{\textquoteright} to circumvent the problem of non-uniform illumination. We used the similarity measure to retrieve similar faces from a database containing multiple images of individuals. Moreover, we devised experiments to study the effect age plays in affecting facial similarity. In conclusion, the similarity measure helps in studying the significance facial features play in affecting the performance of face recognition systems.},
	keywords = {Aging, database, databases;, disguise;, effect;, Expression, Face, half-face;, illumination;, image, lighting;, pose, recognition, recognition;, retrieval;, system;, variation;, visual},
	doi = {10.1109/ICIP.2004.1421474},
	author = {Ramanathan,N. and Chellapa, Rama and Roy Chowdhury, A.K.}
}
@conference {12692,
	title = {Multiple-exemplar discriminant analysis for face recognition},
	booktitle = {Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
	volume = {4},
	year = {2004},
	month = {2004/08//},
	pages = {191 - 194 Vol.4 - 191 - 194 Vol.4},
	abstract = {Face recognition is characteristically different from regular pattern recognition and, therefore, requires a different discriminant analysis other than linear discriminant analysis(LDA). LDA is a single-exemplar method in the sense that each class during classification is represented by a single exemplar, i.e., the sample mean of the class. We present a multiple-exemplar discriminant analysis (MEDA) where each class is represented using several exemplars or even the whole available sample set. The proposed approach produces improved classification results when tested on a subset of FERET database where LDA is ineffective.},
	keywords = {analysis;, database;, databases;, discriminant, Face, FERET, multiple-exemplar, recognition;, visual},
	doi = {10.1109/ICPR.2004.1333736},
	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 {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.}
}
@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}
}
@conference {12718,
	title = {Rank constrained recognition under unknown illuminations},
	booktitle = {Analysis and Modeling of Faces and Gestures, 2003. AMFG 2003. IEEE International Workshop on},
	year = {2003},
	month = {2003/10//},
	pages = {11 - 18},
	abstract = {Recognition under illumination variations is a challenging problem. The key is to successfully separate the illumination source from the observed appearance. Once separated, what remains is invariant to illuminant and appropriate for recognition. Most current efforts employ a Lambertian reflectance model with varying albedo field ignoring both attached and cast shadows, but restrict themselves by using object-specific samples, which undesirably deprives them of recognizing new objects not in the training samples. Using rank constraints on the albedo and the surface normal, we accomplish illumination separation in a more general setting, e.g., with class-specific samples via a factorization approach. In addition, we handle shadows (both attached and cast ones) by treating them as missing values, and resolve the ambiguities in the factorization method by enforcing integrability. As far as recognition is concerned, a bootstrap set which is just a collection of two-dimensional image observations can be utilized to avoid the explicit requirement that three-dimensional information be available. Our approaches produce good recognition results as shown in our experiments using the PIE database.},
	keywords = {albedo, approach;, constrained, database;, databases;, decomposition;, factorization, field;, illumination, image;, information;, Lambertian, lighting;, model;, object, object-specific, PIE, rank, recognition;, reflectance, samples;, singular, three-dimensional, two-dimensional, value, variations;, visual},
	doi = {10.1109/AMFG.2003.1240818},
	author = {Zhou, S. and Chellapa, Rama}
}
@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 {12724,
	title = {View synthesis of articulating humans using visual hull},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {1},
	year = {2003},
	month = {2003/07//},
	pages = {I - 489-92 vol.1 - I - 489-92 vol.1},
	abstract = {In this paper, we present a method, which combines image-based visual hull and human body part segmentation for overcoming the inability of the visual hull method to reconstruct concave regions. The virtual silhouette image corresponding to the given viewing direction is first produced with image-based visual hull. Human body part localization technique is used to segment the input images and the rendered virtual silhouette image into convex body parts. The body parts in the virtual view are generated separately from the corresponding body parts in the input views and then assembled together. The previously rendered silhouette image is used to locate the corresponding body parts in input views and avoid the unconnected or squeezed regions in the assembled final view. Experiments show that this method can improve the reconstruction of concave regions for human postures and texture mapping.},
	keywords = {analysis;, body, convex, gesture, hull;, human, image, image-based, image;, mapping;, MOTION, part, parts;, postures;, recognition;, reconstruction;, segmentation;, silhouette, synthesis;, TEXTURE, texture;, view, virtual, visual},
	doi = {10.1109/ICME.2003.1220961},
	author = {Yue,Zhanfeng and Liang Zhao and Chellapa, Rama}
}
@conference {16914,
	title = {Content-based image retrieval using Fourier descriptors on a logo database},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {521 - 524 vol.3 - 521 - 524 vol.3},
	abstract = {A system that enables the pictorial specification of queries in an image database is described. The queries are comprised of rectangle, polygon, ellipse, and B-spline shapes. The queries specify which shapes should appear in the target image as well as spatial constraints on the distance between them and their relative position. The retrieval process makes use of an abstraction of the contour of the shape which is invariant against translation, scale, rotation, and starting point, that is based on the use of Fourier descriptors. These abstractions are used in a system to locate logos in an image database. The utility of this approach is illustrated using some sample queries.},
	keywords = {abstraction;, analysis;, constraints;, content-based, contour, database, database;, databases;, descriptors;, detection;, edge, Fourier, image, logos;, pictorial, processing;, query, retrieval;, SHAPE, spatial, specification;, theory;, visual},
	doi = {10.1109/ICPR.2002.1047991},
	author = {Folkers,A. and Samet, Hanan}
}
@conference {14961,
	title = {Efficient techniques for range search queries on earth science data},
	booktitle = {Scientific and Statistical Database Management, 2002. Proceedings. 14th International Conference on},
	year = {2002},
	month = {2002///},
	pages = {142 - 151},
	abstract = {We consider the problem of organizing large scale earth science raster data to efficiently handle queries for identifying regions whose parameters fall within certain range values specified by the queries. This problem seems to be critical to enabling basic data mining tasks such as determining associations between physical phenomena and spatial factors, detecting changes and trends, and content based retrieval. We assume that the input is too large to fit in internal memory and hence focus on data structures and algorithms that minimize the I/O bounds. A new data structure, called a tree-of-regions (ToR), is introduced and involves a combination of an R-tree and efficient representation of regions. It is shown that such a data structure enables the handling of range queries in an optimal I/O time, under certain reasonable assumptions. We also show that updates to the ToR can be handled efficiently. Experimental results for a variety of multi-valued earth science data illustrate the fast execution times of a wide range of queries, as predicted by our theoretical analysis.},
	keywords = {based, computing;, content, data, data;, databases;, Earth, factors;, large, mining, mining;, natural, processing;, queries;, query, range, raster, retrieval;, scale, Science, sciences, search, spatial, structures;, tasks;, temporal, tree, tree-of-regions;, visual},
	doi = {10.1109/SSDM.2002.1029714},
	author = {Shi,Qingmin and JaJa, Joseph F.}
}
@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 {14855,
	title = {Stochastic completion fields: a neural model of illusory contour shape and salience},
	booktitle = {Computer Vision, 1995. Proceedings., Fifth International Conference on},
	year = {1995},
	month = {1995/06//},
	pages = {408 - 415},
	abstract = {We describe an algorithm and representation level theory of illusory contour shape and salience. Unlike previous theories, our model is derived from a single assumption-namely, that the prior probability distribution of boundary completion shape can be modeled by a random walk in a lattice whose points are positions and orientations in the image plane (i.e. the space which one can reasonably assume is represented by neurons of the mammalian visual cortex). Our model does not employ numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a particle following a random walk will pass through a given position and orientation on a path joining two boundary fragments can be computed directly as the product of two vector-field convolutions. We show that for the random walk we define, the maximum likelihood paths are curves of least energy, that is, on average, random walks follow paths commonly assumed to model the shape of illusory contours. A computer model is demonstrated on numerous illusory contour stimuli from the literature},
	keywords = {boundary, completion, computational, Computer, contour, contours;, convolutions;, cortex;, curves, detection;, distribution;, edge, energy;, estimation;, fields;, fragments;, geometry;, illusory, image, lattice;, least, likelihood, mammalian, maximum, model;, nets;, neural, of, paths;, plane;, probability, probability;, random, recognition;, shape;, stimuli;, Stochastic, vector-field, visual, walk;},
	doi = {10.1109/ICCV.1995.466910},
	author = {Williams,L. R and Jacobs, David W.}
}
