@article {19275,
	title = {Mapping Parameterized Cyclo-static Dataflow Graphs onto Configurable Hardware},
	journal = {Journal of Signal Processing Systems},
	volume = {66},
	year = {2012},
	month = {2012},
	pages = {285 - 301},
	abstract = {In recent years, parameterized dataflow has evolved as a useful framework for modeling synchronous and cyclo-static graphs in which arbitrary parameters can be changed dynamically. Parameterized dataflow has proven to have significant expressive power for managing dynamics of DSP applications in important ways. However, efficient hardware synthesis techniques for parameterized dataflow representations are lacking. This paper addresses this void; specifically, the paper investigates efficient field programmable gate array (FPGA)-based implementation of parameterized cyclo-static dataflow (PCSDF) graphs. We develop a scheduling technique for throughput-constrained minimization of dataflow buffering requirements when mapping PCSDF representations of DSP applications onto FPGAs. The proposed scheduling technique is integrated with an existing formal schedule model, called the generalized schedule tree, to reduce schedule cost. To demonstrate our new, hardware-oriented PCSDF scheduling technique, we have designed a real-time base station emulator prototype based on a subset of long-term evolution (LTE), which is a key cellular standard.},
	keywords = {4G communication systems, Circuits and Systems, Computer Imaging, Vision, Pattern Recognition and Graphics, Dataflow modeling, Electrical Engineering, FPGA implementation, Image Processing and Computer Vision, Parameterized dataflow, pattern recognition, scheduling, Signal, Image and Speech Processing},
	isbn = {1939-8018, 1939-8115},
	url = {http://link.springer.com/article/10.1007/s11265-011-0599-5},
	author = {Kee, Hojin and Chung-Ching Shen and Bhattacharyya, Shuvra S. and Wong, Ian and Yong Rao and Kornerup, Jacob}
}
@article {14485,
	title = {Eighth workshop on mining and learning with graphs},
	journal = {SIGKDD Explor. Newsl.},
	volume = {12},
	year = {2011},
	month = {2011/03//},
	pages = {63 - 65},
	abstract = {The Eighth Workshop on Mining and Learning with Graphs (MLG)1was held at KDD 2010 in Washington DC. It brought together a variete of researchers interested in analyzing data that is best represented as a graph. Examples include the WWW, social networks, biological networks, communication networks, and many others. The importance of being able to effectively mine and learn from such data is growing, as more and more structured and semi-structured data is becoming available. This is a problem across widely different fields such as economics, statistics, social science, physics and computer science, and is studied within a variety of sub-disciplines of machine learning and data mining including graph mining, graphical models, kernel theory, statistical relational learning, etc. The objective of this workshop was to bring together practitioners from these various fields and areas to foster a rich discussion of which problems we work on, how we frame them in the context of graphs, which tools and algorithms we apply and our general findings and lessons learned. This year{\textquoteright}s workshop was very successful with well over 100 attendees, excellent keynote speakers and papers. This is a rapidly growing area and we believe that this community is only in its infancy. We hope that the readers will join us next year for MLG 2011.},
	keywords = {data mining, dynamic network analysis, graph mining, kernel methods, link mining, machine learning, network analysis, pattern recognition, relational learning, scalable graph mining, statistical relational learning},
	isbn = {1931-0145},
	doi = {10.1145/1964897.1964915},
	url = {http://doi.acm.org/10.1145/1964897.1964915},
	author = {Brefeld,Ulf and Getoor, Lise and Macskassy,Sofus A.}
}
@conference {12438,
	title = {The evolution of stochastic grammars for representation and recognition of activities in videos},
	booktitle = {2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)},
	year = {2011},
	month = {2011/11/06/13},
	pages = {688 - 688},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The speaker is one of the privileged many to have been taught syntactic pattern recognition methods by the Late Prof. K.S. Fu. In this talk, I will discuss the evolution of stochastic image grammars from the early seventies to now with a focus on image and video understanding applications.},
	keywords = {activity recognition, activity representation, Conferences, Educational institutions, Grammar, Image analysis, image recognition, image representation, image understanding, pattern recognition, stochastic image grammars, syntactic pattern recognition methods, video signal processing, video understanding, Videos},
	isbn = {978-1-4673-0062-9},
	doi = {10.1109/ICCVW.2011.6130309},
	author = {Chellapa, Rama}
}
@article {19272,
	title = {Exploiting Statically Schedulable Regions in Dataflow Programs},
	journal = {Journal of Signal Processing Systems},
	volume = {63},
	year = {2011},
	month = {2011},
	pages = {129 - 142},
	abstract = {Dataflow descriptions have been used in a wide range of Digital Signal Processing (DSP) applications, such as multi-media processing, and wireless communications. Among various forms of dataflow modeling, Synchronous Dataflow (SDF) is geared towards static scheduling of computational modules, which improves system performance and predictability. However, many DSP applications do not fully conform to the restrictions of SDF modeling. More general dataflow models, such as CAL (Eker and Janneck 2003), have been developed to describe dynamically-structured DSP applications. Such generalized models can express dynamically changing functionality, but lose the powerful static scheduling capabilities provided by SDF. This paper focuses on the detection of SDF-like regions in dynamic dataflow descriptions{\textemdash}in particular, in the generalized specification framework of CAL. This is an important step for applying static scheduling techniques within a dynamic dataflow framework. Our techniques combine the advantages of different dataflow languages and tools, including CAL (Eker and Janneck 2003), DIF (Hsu et al. 2005) and CAL2C (Roquier et al. 2008). In addition to detecting SDF-like regions, we apply existing SDF scheduling techniques to exploit the static properties of these regions within enclosing dynamic dataflow models. Furthermore, we propose an optimized approach for mapping SDF-like regions onto parallel processing platforms such as multi-core processors.},
	keywords = {Cal, Circuits and Systems, Computer Imaging, Vision, Pattern Recognition and Graphics, Dataflow, DIF, Electrical Engineering, Image Processing and Computer Vision, multicore processors, pattern recognition, Quasi-static scheduling, Signal, Image and Speech Processing},
	isbn = {1939-8018, 1939-8115},
	url = {http://link.springer.com/article/10.1007/s11265-009-0445-1},
	author = {Gu, Ruirui and Janneck, J{\"o}rn W. and Raulet, Micka{\"e}l and Bhattacharyya, Shuvra S.}
}
@conference {12218,
	title = {IP geolocation in metropolitan areas},
	booktitle = {Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems},
	series = {SIGMETRICS {\textquoteright}11},
	year = {2011},
	month = {2011///},
	pages = {155 - 156},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Current IP geoloation techniques can geolocate an IP address to a region approximately 700 square miles, roughly the size of a metropolitan area. We model geolocation as a pattern-recognition problem, and introduce techniques that geolocate addresses to within 5 miles inside a metropolitan area. We propose two complementary algorithms: The first algorithm, Pattern Based Geolocation (PBG), models the distribution of latencies to the target and compares it to those of the reference landmarks to resolve an address to within 5 miles in a metropolitan area. The second approach, Perturbation Augmented PBG (PAPBG), provides higher resolution by sending extra traffic in the network. While sending an aggregate of 600 Kbps extra traffic to 20 nodes for approximately 2 minutes, PAPBG geolocates addresses to within 3 miles.},
	keywords = {geolocation, pattern recognition, perturbation},
	isbn = {978-1-4503-0814-4},
	doi = {10.1145/1993744.1993803},
	url = {http://doi.acm.org/10.1145/1993744.1993803},
	author = {Singh,Satinder Pal and Baden,Randolph and Lee,Choon and Bhattacharjee, Bobby and La,Richard and Shayman,Mark}
}
@article {19271,
	title = {Overview of the MPEG Reconfigurable Video Coding Framework},
	journal = {Journal of Signal Processing Systems},
	volume = {63},
	year = {2011},
	month = {2011},
	pages = {251 - 263},
	abstract = {Video coding technology in the last 20 years has evolved producing a variety of different and complex algorithms and coding standards. So far the specification of such standards, and of the algorithms that build them, has been done case by case providing monolithic textual and reference software specifications in different forms and programming languages. However, very little attention has been given to provide a specification formalism that explicitly presents common components between standards, and the incremental modifications of such monolithic standards. The MPEG Reconfigurable Video Coding (RVC) framework is a new ISO standard currently under its final stage of standardization, aiming at providing video codec specifications at the level of library components instead of monolithic algorithms. The new concept is to be able to specify a decoder of an existing standard or a completely new configuration that may better satisfy application-specific constraints by selecting standard components from a library of standard coding algorithms. The possibility of dynamic configuration and reconfiguration of codecs also requires new methodologies and new tools for describing the new bitstream syntaxes and the parsers of such new codecs. The RVC framework is based on the usage of a new actor/ dataflow oriented language called CAL for the specification of the standard library and instantiation of the RVC decoder model. This language has been specifically designed for modeling complex signal processing systems. CAL dataflow models expose the intrinsic concurrency of the algorithms by employing the notions of actor programming and dataflow. The paper gives an overview of the concepts and technologies building the standard RVC framework and the non standard tools supporting the RVC model from the instantiation and simulation of the CAL model to software and/or hardware code synthesis.},
	keywords = {CAL actor language, Circuits and Systems, Code synthesis, Computer Imaging, Vision, Pattern Recognition and Graphics, Dataflow programming, Electrical Engineering, Image Processing and Computer Vision, pattern recognition, Reconfigurable Video Coding, Signal, Image and Speech Processing},
	isbn = {1939-8018, 1939-8115},
	url = {http://link.springer.com/article/10.1007/s11265-009-0399-3},
	author = {Bhattacharyya, Shuvra S. and Eker, Johan and Janneck, J{\"o}rn W. and Lucarz, Christophe and Mattavelli, Marco and Raulet, Micka{\"e}l}
}
@article {15907,
	title = {Sparsity-motivated automatic target recognition},
	journal = {Applied OpticsAppl. Opt.},
	volume = {50},
	year = {2011},
	month = {2011/04/01/},
	pages = {1425 - 1433},
	abstract = {We present an automatic target recognition algorithm using the recently developed theory of sparse representations and compressive sensing. We show how sparsity can be helpful for efficient utilization of data for target recognition. We verify the efficacy of the proposed algorithm in terms of the recognition rate and confusion matrices on the well known Comanche (Boeing{\textendash}Sikorsky, USA) forward-looking IR data set consisting of ten different military targets at different orientations.},
	keywords = {IMAGE PROCESSING, Image recognition, algorithms and filters, pattern recognition, Vision - patterns and recognition},
	doi = {10.1364/AO.50.001425},
	url = {http://ao.osa.org/abstract.cfm?URI=ao-50-10-1425},
	author = {Patel, Vishal M. and Nasrabadi,Nasser M. and Chellapa, Rama}
}
@article {19256,
	title = {Topological Patterns for Scalable Representation and Analysis of Dataflow Graphs},
	journal = {Journal of Signal Processing Systems},
	volume = {65},
	year = {2011},
	month = {2011},
	pages = {229 - 244},
	abstract = {Tools for designing signal processing systems with their semantic foundation in dataflow modeling often use high-level graphical user interfaces (GUIs) or text based languages that allow specifying applications as directed graphs. Such graphical representations serve as an initial reference point for further analysis and optimizations that lead to platform-specific implementations. For large-scale applications, the underlying graphs often consist of smaller substructures that repeat multiple times. To enable more concise representation and direct analysis of such substructures in the context of high level DSP specification languages and design tools, we develop the modeling concept of topological patterns, and propose ways for supporting this concept in a high-level language. We augment the dataflow interchange format (DIF) language{\textemdash}a language for specifying DSP-oriented dataflow graphs{\textemdash}with constructs for supporting topological patterns, and we show how topological patterns can be effective in various aspects of embedded signal processing design flows using specific application examples.},
	keywords = {Circuits and Systems, Computer Imaging, Vision, Pattern Recognition and Graphics, Dataflow graphs, Electrical Engineering, High-level languages, Image Processing and Computer Vision, model-based design, pattern recognition, Signal processing systems, Signal, Image and Speech Processing, Topological patterns},
	isbn = {1939-8018, 1939-8115},
	url = {http://link.springer.com/article/10.1007/s11265-011-0610-1},
	author = {Sane, Nimish and Kee, Hojin and Seetharaman, Gunasekaran and Bhattacharyya, Shuvra S.}
}
@conference {15918,
	title = {Sectored Random Projections for Cancelable Iris Biometrics},
	booktitle = {2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)},
	year = {2010},
	month = {2010/03//},
	pages = {1838 - 1841},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Privacy and security are essential requirements in practical biometric systems. In order to prevent the theft of biometric patterns, it is desired to modify them through revocable and non invertible transformations called Cancelable Biometrics. In this paper, we propose an efficient algorithm for generating a Cancelable Iris Biometric based on Sectored Random Projections. Our algorithm can generate a new pattern if the existing one is stolen, retain the original recognition performance and prevent extraction of useful information from the transformed patterns. Our method also addresses some of the drawbacks of existing techniques and is robust to degradations due to eyelids and eyelashes.},
	keywords = {biometric pattern, Biometrics, Cancelable Biometrics, cancelable iris biometrics, data mining, data privacy, Degradation, Eyelashes, Eyelids, Iris, iris recognition, pattern recognition, privacy, random processes, Random Projections, Robustness, sectored random projection, Secure Biometrics, Security, security of data},
	isbn = {978-1-4244-4295-9},
	doi = {10.1109/ICASSP.2010.5495383},
	author = {Pillai,J.K. and Patel, Vishal M. and Chellapa, Rama and Ratha,N. K}
}
@conference {16951,
	title = {A Visual Interface for Multivariate Temporal Data: Finding Patterns of Events across Multiple Histories},
	booktitle = {Visual Analytics Science And Technology, 2006 IEEE Symposium On},
	year = {2006},
	month = {2006/11/31/Oct. },
	pages = {167 - 174},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Finding patterns of events over time is important in searching patient histories, Web logs, news stories, and criminal activities. This paper presents PatternFinder, an integrated interface for query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets. We define temporal patterns as sequences of events with inter-event time spans. PatternFinder allows users to specify the attributes of events and time spans to produce powerful pattern queries that are difficult to express with other formalisms. We characterize the range of queries PatternFinder supports as users vary the specificity at which events and time spans are defined. Pattern Finder{\textquoteright}s query capabilities together with coupled ball-and-chain and tabular visualizations enable users to effectively query, explore and analyze event patterns both within and across data entities (e.g. patient histories, terrorist groups, Web logs, etc.)},
	keywords = {ball-and-chain visualization, Chromium, Computer science, Data analysis, data visualisation, Data visualization, Database languages, event pattern discovery, Graphical user interfaces, History, Information Visualization, Medical treatment, multivariate temporal data, Pattern analysis, pattern recognition, PatternFinder integrated interface, Query processing, query visualization, result-set visualization, Spatial databases, tabular visualization, temporal pattern discovery, temporal pattern searching, Temporal query, user interface, User interfaces, visual databases, visual interface},
	isbn = {1-4244-0591-2},
	doi = {10.1109/VAST.2006.261421},
	author = {Fails,J. A and Karlson,A. and Shahamat,L. and Shneiderman, Ben}
}
@article {12660,
	title = {Image-based face recognition under illumination and pose variations},
	journal = {Journal of the Optical Society of America AJ. Opt. Soc. Am. A},
	volume = {22},
	year = {2005},
	month = {2005/02/01/},
	pages = {217 - 229},
	abstract = {We present an image-based method for face recognition across different illuminations and poses, where the term image-based means that no explicit prior three-dimensional models are needed. As face recognition under illumination and pose variations involves three factors, namely, identity, illumination, and pose, generalizations in all these three factors are desired. We present a recognition approach that is able to generalize in the identity and illumination dimensions and handle a given set of poses. Specifically, the proposed approach derives an identity signature that is illumination- and pose-invariant, where the identity is tackled by means of subspace encoding, the illumination is characterized with a Lambertian reflectance model, and the given set of poses is treated as a whole. Experimental results using the Pose, Illumination, and Expression (PIE) database demonstrate the effectiveness of the proposed approach.},
	keywords = {illumination, pattern recognition},
	doi = {10.1364/JOSAA.22.000217},
	url = {http://josaa.osa.org/abstract.cfm?URI=josaa-22-2-217},
	author = {Zhou,Shaohua Kevin and Chellapa, Rama}
}
@article {17913,
	title = {Unsupervised learning applied to progressive compression of time-dependent geometry},
	journal = {Computers \& Graphics},
	volume = {29},
	year = {2005},
	month = {2005/06//},
	pages = {451 - 461},
	abstract = {We propose a new approach to progressively compress time-dependent geometry. Our approach exploits correlations in motion vectors to achieve better compression. We use unsupervised learning techniques to detect good clusters of motion vectors. For each detected cluster, we build a hierarchy of motion vectors using pairwise agglomerative clustering, and succinctly encode the hierarchy using entropy encoding. We demonstrate our approach on a client{\textendash}server system that we have built for downloading time-dependent geometry.},
	keywords = {Clustering algorithms, Distributed/network graphics, pattern recognition},
	isbn = {0097-8493},
	doi = {10.1016/j.cag.2005.03.021},
	url = {http://www.sciencedirect.com/science/article/pii/S009784930500052X},
	author = {Baby,Thomas and Kim,Youngmin and Varshney, Amitabh}
}
@article {13223,
	title = {Gait recognition using image self-similarity},
	journal = {EURASIP J. Appl. Signal Process.},
	volume = {2004},
	year = {2004},
	month = {2004/01//},
	pages = {572 - 585},
	abstract = {Gait is one of the few biometrics that can be measured at a distance, and is hence useful for passive surveillance as well as biometric applications. Gait recognition research is still at its infancy, however, and we have yet to solve the fundamental issue of finding gait features which at once have suffcient discrimination power and can be extracted robustly and accurately from low-resolution video. This paper describes a novel gait recognition technique based on the image self-similarity of a walking person. We contend that the similarity plot encodes a projection of gait dynamics. It is also correspondence-free, robust to segmentation noise, and works well with low-resolution video. The method is tested on multiple data sets of varying sizes and degrees of diffculty. Performance is best for fronto-parallel viewpoints, whereby a recognition rate of 98\% is achieved for a data set of 6 people, and 70\% for a data set of 54 people.},
	keywords = {behavioral biometrics, gait recognition, human identification at a distance, human movement analysis, pattern recognition},
	isbn = {1110-8657},
	doi = {10.1155/S1110865704309236},
	url = {http://dx.doi.org/10.1155/S1110865704309236},
	author = {BenAbdelkader,Chiraz and Cutler,Ross G. and Davis, Larry S.}
}
@inbook {19651,
	title = {An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets},
	booktitle = {Computer Vision - ECCV 2004},
	series = {Lecture Notes in Computer Science},
	year = {2004},
	month = {2004/01/01/},
	pages = {279 - 290},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	abstract = {We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such interactions cause problems for traditional approaches to the data association problem. In response, we developed a joint tracker that includes a more sophisticated motion model to maintain the identity of targets throughout an interaction, drastically reducing tracker failures. The paper presents two main contributions: (1) we show how a Markov random field (MRF) motion prior, built on the fly at each time step, can substantially improve tracking when targets interact, and (2) we show how this can be done efficiently using Markov chain Monte Carlo (MCMC) sampling. We prove that incorporating an MRF to model interactions is equivalent to adding an additional interaction factor to the importance weights in a joint particle filter. Since a joint particle filter suffers from exponential complexity in the number of tracked targets, we replace the traditional importance sampling step in the particle filter with an MCMC sampling step. The resulting filter deals efficiently and effectively with complicated interactions when targets approach each other. We present both qualitative and quantitative results to substantiate the claims made in the paper, including a large scale experiment on a video-sequence of over 10,000 frames in length.},
	keywords = {Artificial Intelligence (incl. Robotics), Computer Graphics, Image Processing and Computer Vision, pattern recognition},
	isbn = {978-3-540-21981-1, 978-3-540-24673-2},
	url = {http://link.springer.com/chapter/10.1007/978-3-540-24673-2_23},
	author = {Zia Khan and Balch, Tucker and Dellaert, Frank},
	editor = {Pajdla, Tom{\'a}s and Matas, Ji{\v r}{\'\i}}
}
@conference {17113,
	title = {Dynamic querying for pattern identification in microarray and genomic data},
	booktitle = {2003 International Conference on Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings},
	volume = {3},
	year = {2003},
	month = {2003/07/06/9},
	pages = {III- 453-6 vol.3 - III- 453-6 vol.3},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Data sets involving linear ordered sequences are a recurring theme in bioinformatics. Dynamic query tools that support exploration of these data sets can be useful for identifying patterns of interest. This paper describes the use of one such tool - timesearcher - to interactively explore linear sequence data sets taken from two bioinformatics problems. Microarray time course data sets involve expression levels for large numbers of genes over multiple time points. Timesearcher can be used to interactively search these data sets for genes with expression profiles of interest. The occurrence frequencies of short sequences of DNA in aligned exons can be used to identify sequences that play a role in the pre-mRNA splicing. Timesearcher can be used to search these data sets for candidate splicing signals.},
	keywords = {Bioinformatics, data sets, Displays, dynamic querying, expression profiles, Frequency, Gene expression, genes, Genetics, genomic data, Genomics, linear ordered sequences, macromolecules, medical signal processing, Mice, Microarray, pattern identification, pattern recognition, premRNA splicing, Query processing, sequences, Signal processing, splicing, TimeSearcher},
	isbn = {0-7803-7965-9},
	doi = {10.1109/ICME.2003.1221346},
	author = {Hochheiser,H. and Baehrecke,E. H and Mount, Stephen M. and Shneiderman, Ben}
}
@conference {11894,
	title = {Hidden Markov models for silhouette classification},
	booktitle = {Automation Congress, 2002 Proceedings of the 5th Biannual World},
	volume = {13},
	year = {2002},
	month = {2002///},
	pages = {395 - 402},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with other techniques that use hidden Markov models for object classification from silhouettes is presented.},
	keywords = {Computer vision, Feature extraction, Fourier transforms, hidden Markov models, HMM, image classification, Neural networks, object classification, Object recognition, parameter estimation, pattern recognition, Probability distribution, Shape measurement, silhouette classification, Wavelet transforms},
	isbn = {1-889335-18-5},
	doi = {10.1109/WAC.2002.1049575},
	author = {Abd-Almageed, Wael and Smith,C.}
}
@article {15568,
	title = {Chromatic nearest neighbor searching: A query sensitive approach},
	journal = {Computational Geometry},
	volume = {17},
	year = {2000},
	month = {2000/12//},
	pages = {97 - 119},
	abstract = {The nearest neighbor problem is that of preprocessing a set P of n data points in Rd so that, given any query point q, the closest point in P to q can be determined efficiently. In the chromatic nearest neighbor problem, each point of P is assigned a color, and the problem is to determine the color of the nearest point to the query point. More generally, given k⩾1, the problem is to determine the color occurring most frequently among the k nearest neighbors. The chromatic version of the nearest neighbor problem is used in many applications in pattern recognition and learning. In this paper we present a simple algorithm for solving the chromatic k nearest neighbor problem. We provide a query sensitive analysis, which shows that if the color classes form spatially well separated clusters (as often happens in practice), then queries can be answered quite efficiently. We also allow the user to specify an error bound ε⩾0, and consider the same problem in the context of approximate nearest neighbor searching. We present empirical evidence that for well clustered data sets, this approach leads to significant improvements in efficiency.},
	keywords = {BBD trees, Branch-and-bound search, Chromatic nearest neighbors, Classification algorithms, Multidimensional searching, pattern recognition, Query sensitive analysis},
	isbn = {0925-7721},
	doi = {10.1016/S0925-7721(00)00021-3},
	url = {http://www.sciencedirect.com/science/article/pii/S0925772100000213},
	author = {Mount, Dave and Netanyahu,Nathan S. and Silverman,Ruth and Wu,Angela Y.}
}
@article {14189,
	title = {A syntactic approach to scale-space-based corner description},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {16},
	year = {1994},
	month = {1994/07//},
	pages = {748 - 751},
	abstract = {Planar curves are described by information about corners integrated over various levels of resolution. The detection of corners takes place on a digital representation. To compensate for ambiguities arising from sampling problems due to the discreteness, results about the local behavior of curvature extrema in continuous scale-space are employed},
	keywords = {Computer vision, corner detection, curvature extrema, edge detection, IMAGE PROCESSING, image resolution, Image segmentation, Laboratories, Large-scale systems, PARALLEL PROCESSING, pattern recognition, planar curves, resolution, Sampling methods, sampling problems, scale space based corner description, SHAPE, Smoothing methods, syntactic approach},
	isbn = {0162-8828},
	doi = {10.1109/34.297957},
	author = {Ferm{\"u}ller, Cornelia and Kropatsch,W.}
}
@conference {14246,
	title = {Perceptual computational advantages of tracking},
	booktitle = {, 11th IAPR International Conference on Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings},
	year = {1992},
	month = {1992/09/30/Aug-3},
	pages = {599 - 602},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The paradigm of active vision advocates studying visual problems in the form of modules that are directly related to a visual task for observers that are active. It is argued that in many cases when an object is moving in an unrestricted manner (translation and rotation) in the 3D world only the motion{\textquoteright}s translational components are of interest. For a monocular observer, using only the normal flow-the spatiotemporal derivatives of the image intensity function-the authors solve the problem of computing the direction of translation. Their strategy uses fixation and tracking. Fixation simplifies much of the computation by placing the object at the center of the visual field, and the main advantage of tracking is the accumulation of information over time. The authors show how tracking is accomplished using normal flow measurements and use it for two different tasks in the solution process. First, it serves as a tool to compensate for the lack of existence of an optical flow field and thus to estimate the translation parallel to the image plane; and second, it gathers information about the motion component perpendicular to the image plane},
	keywords = {active vision, Automation, Employment, fixation, image intensity function, Image motion analysis, IMAGE PROCESSING, Motion estimation, Nonlinear optics, Optical computing, Optical sensors, parameter estimation, pattern recognition, perceptual computational advantages, spatiotemporal derivatives, Spatiotemporal phenomena, tracking, unrestricted motion, visual flow measurements},
	isbn = {0-8186-2910-X},
	doi = {10.1109/ICPR.1992.201633},
	author = {Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {18307,
	title = {3D object recognition via simulated particles diffusion},
	booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1989. Proceedings CVPR {\textquoteright}89},
	year = {1989},
	month = {1989/06//},
	pages = {442 - 449},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A novel approach for 3D object recognition is presented. This approach is model-based, and assumes either 3D or 21/2 D scene acquisition. Transformation detection is accomplished along with an object identification (six degrees of freedom, three rotational and three translational, are assumed). The diffusion-like simulation recently introduced as a means for characterization of shape is used in the extraction of point features. The point features represent regions on the object{\textquoteright}s surface that are extreme in curvature (i.e. concavities and convexities). Object matching is carried out by examining the correspondence between the object{\textquoteright}s set of point features and the model{\textquoteright}s set of point features, using an alignment strategy. Triangles are constructed between all possible triples of object{\textquoteright}s point features, and then are aligned to candidate corresponding triangles of the model{\textquoteright}s point features. 21/2 range images are transformed into a volumetric representation through a parallel projection onto the 3-D space. The resultant volume is suitable for processing by the diffusion-like simulation},
	keywords = {3D object recognition, alignment strategy, Computational modeling, Computer science, data mining, Gold, Layout, Noise shaping, Object detection, Object recognition, parallel projection, pattern recognition, point features, radio access networks, scene acquisition, shape characterisation, Shape measurement, simulated particles diffusion, transformation detection},
	isbn = {0-8186-1952-x},
	doi = {10.1109/CVPR.1989.37886},
	author = {Yacoob,Yaser and Gold,Y. I}
}
