Visual Object Tracking

Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target. In this chapter, we first introduce the moving object detection method in static background. We also present the Adaptive background modeling method by using a mixture Gaussians. In the next three sections, there are three methods for object tracking: Ransac, Meanshift and Particle Filter. In the last section, we introduce the multi-object tracking method.

[1]  Zhenjiang Miao,et al.  Fast Background Subtraction and Shadow Elimination Using Improved Gaussian Mixture Model , 2007, 2007 IEEE International Workshop on Haptic, Audio and Visual Environments and Games.

[2]  Reinhard Klette,et al.  Robust background subtraction and maintenance , 2004, ICPR 2004.

[3]  Harry Shum,et al.  Color sketch generation , 2006, NPAR.

[4]  Leopoldo Angrisani,et al.  Unscented transform: a powerful tool for measurement uncertainty evaluation , 2005, IEEE Transactions on Instrumentation and Measurement.

[5]  Yoshiki Ninomiya,et al.  Pedestrian Detection for a Near Infrared Imaging System , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[6]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[7]  Ying Wang,et al.  Abnormal Activity Recognition in Office Based on R Transform , 2007, 2007 IEEE International Conference on Image Processing.

[8]  Max A. Viergever,et al.  Probabilistic Multiscale Image Segmentation , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  David A. Forsyth,et al.  Finding and tracking people from the bottom up , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[10]  Franklin C. Crow,et al.  Summed-area tables for texture mapping , 1984, SIGGRAPH.

[11]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Roberto Brunelli,et al.  Template Matching Techniques in Computer Vision: Theory and Practice , 2009 .

[13]  Narendra Ahuja,et al.  Multiscale image segmentation by integrated edge and region detection , 1997, IEEE Trans. Image Process..

[14]  Anton van den Hengel,et al.  Fast Global Kernel Density Mode Seeking: Applications to Localization and Tracking , 2007, IEEE Transactions on Image Processing.

[15]  Kim L. Boyer,et al.  The laplacian-of-gaussian kernel: A formal analysis and design procedure for fast, accurate convolution and full-frame output , 1989, Comput. Vis. Graph. Image Process..

[16]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[17]  Ishwar K. Sethi,et al.  Finding Trajectories of Feature Points in a Monocular Image Sequence , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Lyudmila Mihaylova,et al.  Extended Object Tracking Using Monte Carlo Methods , 2008, IEEE Transactions on Signal Processing.

[19]  Janne Heikkilä,et al.  Intensity independent color models and visual tracking , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[20]  Mubarak Shah,et al.  Establishing motion correspondence , 1991, CVGIP Image Underst..

[21]  Daniel Cremers,et al.  Nonlinear Shape Statistics in Mumford-Shah Based Segmentation , 2002, ECCV.

[22]  Rama Chellappa,et al.  Attribute Grammar-Based Event Recognition and Anomaly Detection , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[23]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[24]  Vinod Chandran,et al.  Automated recognition of drunk driving on highways from video sequences , 1994, Proceedings of 1st International Conference on Image Processing.

[25]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[26]  Fernando Soares,et al.  Watershed lines suppression by waterfall marker improvement and line-neighbourhood analysis , 2004, ICPR 2004.

[27]  Jianwei Zhang,et al.  Multimodal People Tracking and Trajectory Prediction based on Learned Generalized Motion Patterns , 2006, 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

[28]  Ying-Tung Hsiao,et al.  A contour based image segmentation algorithm using morphological edge detection , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[29]  Hans P. Morevec.  Towards automatic visual obstacle avoidance , 1977, IJCAI 1977.

[30]  Yangsheng Xu,et al.  Abnormal Behavior Detection by Multi-SVM-Based Bayesian Network , 2007, 2007 International Conference on Information Acquisition.

[31]  Yan-Ning Zhang,et al.  Activity Analysis Based on SOM , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[32]  Richard G. Baraniuk,et al.  Multiscale image segmentation using wavelet-domain hidden Markov models , 2001, IEEE Trans. Image Process..

[33]  Kevin Nickels,et al.  Weighting observations: the use of kinematic models in object tracking , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[34]  Kenji Suzuki,et al.  Fast connected-component labeling based on sequential local operations in the course of forward raster scan followed by backward raster scan , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[35]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[36]  Nikos Paragios,et al.  Motion-based background subtraction using adaptive kernel density estimation , 2004, CVPR 2004.

[37]  Gang-Zeng Mao,et al.  Real-Time Hand Detection and Tracking against Complex Background , 2009, IIH-MSP.

[38]  Dani Gamerman,et al.  Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference , 1997 .

[39]  Gregory D. Hager,et al.  Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[40]  Tobi Delbrück,et al.  CAVIAR: A 45k Neuron, 5M Synapse, 12G Connects/s AER Hardware Sensory–Processing– Learning–Actuating System for High-Speed Visual Object Recognition and Tracking , 2009, IEEE Transactions on Neural Networks.

[41]  Zhiming Liu,et al.  A skin detector based on neural network , 2002, IEEE 2002 International Conference on Communications, Circuits and Systems and West Sino Expositions.

[42]  Mark W. Woolrich,et al.  Variational bayes inference of spatial mixture models for segmentation , 2006, IEEE Transactions on Medical Imaging.

[43]  Guillermo Sapiro,et al.  Tracking of moving objects under severe and total occlusions , 2005, IEEE International Conference on Image Processing 2005.

[44]  Robert T. Collins,et al.  Mean-shift blob tracking through scale space , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[45]  B. Zhang,et al.  A method for calibrating the central catadioptric camera via Homographic matrix , 2008, 2008 International Conference on Information and Automation.

[46]  Alex Pentland,et al.  Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[47]  Maneesh Dewan.  Toward Optimal Kernel-based Tracking , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[48]  David C. Hogg,et al.  Learning the distribution of object trajectories for event recognition , 1996, Image Vis. Comput..

[49]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[50]  Yuxin Peng,et al.  Color Model based real-time Face Detection with AdaBoost in color image , 2007, 2007 International Conference on Machine Vision.

[51]  Lionel Oisel,et al.  One-dimensional dense disparity estimation for three-dimensional reconstruction , 2003, IEEE Trans. Image Process..

[52]  Robert B. Fisher,et al.  Modelling Crowd Scenes for Event Detection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[53]  Bohyung Han,et al.  On-line density-based appearance modeling for object tracking , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[54]  W. Menzel,et al.  Cloud Tracking with Satellite Imagery: From the Pioneering Work of Ted Fujita to the Present , 2001 .

[55]  Pascal Fua,et al.  Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Multiple Object Tracking Using K-shortest Paths Optimization , 2022 .

[56]  A. Kummert,et al.  A vehicle detection system based on Haar and Triangle features , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[57]  Alain Trémeau,et al.  Regions adjacency graph applied to color image segmentation , 2000, IEEE Trans. Image Process..

[58]  Rimon Elias.  Wide baseline matching through homographic transformation , 2004, ICPR 2004.

[59]  Ming-Hsuan Yang,et al.  Robust Object Tracking with Online Multiple Instance Learning , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[60]  Olac Fuentes,et al.  An object detection system using image reconstruction with PCA , 2005, The 2nd Canadian Conference on Computer and Robot Vision (CRV'05).

[61]  Tim J. Ellis,et al.  Path detection in video surveillance , 2002, Image Vis. Comput..

[62]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[63]  Gregory Hager,et al.  Multiple kernel tracking with SSD , 2004, CVPR 2004.

[64]  B. S. Manjunath,et al.  A Condition Number for Point Matching with Application to Registration and Postregistration Error Estimation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[65]  Josef Kittler,et al.  Region growing: a new approach , 1998, IEEE Trans. Image Process..

[66]  Frank Dellaert,et al.  Model-based car tracking integrated with a road-follower , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[67]  Wenzhan Dai,et al.  Study of occlusions problem in stereo vision , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[68]  P. S. Sastry,et al.  Abnormal activity detection in video sequences using learnt probability densities , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[69]  Joachim Denzler,et al.  Entropy based camera control for visual object tracking , 2002, Proceedings. International Conference on Image Processing.

[70]  Patrick Bouthemy,et al.  Real-Time Tracking of Moving Persons by Exploiting Spatio-Temporal Image Slices , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[71]  Wenhan Luo,et al.  Multiple object tracking: A literature review , 2014, Artif. Intell..

[72]  Baozong Yuan,et al.  A new algorithm for static camera foreground segmentation via active coutours and GMM , 2008, 2008 19th International Conference on Pattern Recognition.

[73]  G. Salut,et al.  Non-overlapping deterministic Gaussian particles in maximum likelihood non-linear filtering: phase tracking application , 2005, 2005 International Symposium on Intelligent Signal Processing and Communication Systems.

[74]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[75]  Stanley T. Birchfield,et al.  Spatiograms versus histograms for region-based tracking , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[76]  Yangsheng Xu,et al.  Crowd Energy and Feature Analysis , 2007, 2007 IEEE International Conference on Integration Technology.

[77]  Jianbo Shi,et al.  Detecting unusual activity in video , 2004, CVPR 2004.

[78]  Bradley P. Carlin,et al.  BAYES AND EMPIRICAL BAYES METHODS FOR DATA ANALYSIS , 1996, Stat. Comput..

[79]  Sean Dougherty,et al.  Edge Detector Evaluation Using Empirical ROC Curves , 2001, Comput. Vis. Image Underst..

[80]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[81]  Etienne E. Kerre,et al.  Using Similarity Measures for Histogram Comparison , 2003, IFSA.

[82]  Bo Thiesson,et al.  Image and Video Segmentation by Anisotropic Kernel Mean Shift , 2004, ECCV.

[83]  Adilson Gonzaga,et al.  Hand Image Segmentation in Video Sequence by GMM: a comparative analysis , 2006, 2006 19th Brazilian Symposium on Computer Graphics and Image Processing.

[84]  Yang Lu,et al.  Online Object Tracking, Learning, and Parsing with And-Or Graphs , 2014, CVPR.

[85]  Stephan Schraml,et al.  Spatiotemporal multiple persons tracking using Dynamic Vision Sensor , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[86]  Jun S. Liu,et al.  Sequential Imputations and Bayesian Missing Data Problems , 1994 .

[87]  Giovanni Garibotto,et al.  3D scene analysis by real-time stereovision , 2005, IEEE International Conference on Image Processing 2005.

[88]  Anton van den Hengel,et al.  Fast global kernel density mode seeking with application to localization and tracking , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[89]  S. A. Benk.  Psycho-visual model of the human optical system as base for lossy-lossless compression of visual information , 2001, 5th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service. TELSIKS 2001. Proceedings of Papers (Cat. No.01EX517).

[90]  Nicolas Martel-Brisson,et al.  Learning and Removing Cast Shadows through a Multidistribution Approach , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[91]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[92]  Yaser Sheikh,et al.  Bayesian modeling of dynamic scenes for object detection , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[93]  Zhu Hao,et al.  Vision-Based Interface: Using Face and Eye Blinking Tracking with Camera , 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

[94]  Guo-Hui Li,et al.  A Probabilistic Model for Surveillance Video Mining , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[95]  M. Clabian,et al.  Single camera lane detection and tracking , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[96]  Takeo Kanade,et al.  Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[97]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.

[98]  A. Leonardis,et al.  Robust localization using eigenspace of spinning-images , 2000, Proceedings IEEE Workshop on Omnidirectional Vision (Cat. No.PR00704).

[99]  Shai Avidan.  Ensemble Tracking , 2007, IEEE Trans. Pattern Anal. Mach. Intell..

[100]  Jia Yunde,et al.  Trinocular Cooperative Stereo Vision and Occlusion Detection , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.

[101]  Mubarak Shah,et al.  An integrated approach for generic object detection using kernel PCA and boosting , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[102]  Gerhard Rigoll,et al.  A flexible multimodal object tracking system , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[103]  Mark Hedley,et al.  Fast corner detection , 1998, Image Vis. Comput..

[104]  N. Richard,et al.  Integration of human perception for color texture management , 2005, International Symposium on Signals, Circuits and Systems, 2005. ISSCS 2005..

[105]  Simone Calderara,et al.  Detection of abnormal behaviors using a mixture of Von Mises distributions , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[106]  Rama Chellappa,et al.  Principal components null space analysis for image and video classification , 2006, IEEE Transactions on Image Processing.

[107]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[108]  A. Leonardis,et al.  Illumination Insensitive Eigenspaces , 2001, ICCV.

[109]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[110]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[111]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[112]  Scott T. Acton,et al.  Motion gradient vector flow: an external force for tracking rolling leukocytes with shape and size constrained active contours , 2004, IEEE Transactions on Medical Imaging.

[113]  Franco Oberti,et al.  Robust tracking of humans and vehicles in cluttered scenes with occlusions , 2002, Proceedings. International Conference on Image Processing.

[114]  Liang Zhao,et al.  Qualitative and quantitative car tracking from a range image sequence , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[115]  Abdesselam Bouzerdoum,et al.  A stochastic competitive learning algorithm , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[116]  Ishwar K. Sethi,et al.  Feature Point Correspondence in the Presence of Occlusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[117]  Leslie Novak.  Optimal Target t Designation Techniques , 1981, IEEE Transactions on Aerospace and Electronic Systems.

[118]  Avinash C. Kak,et al.  Hierarchical Data Structure for Real-Time Background Subtraction , 2006, 2006 International Conference on Image Processing.

[119]  Dorin Comaniciu,et al.  Robust analysis of feature spaces: color image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[120]  Steven M. LaValle,et al.  A Bayesian Segmentation Methodology for Parametric Image Models , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[121]  D. Comaniciu,et al.  The variable bandwidth mean shift and data-driven scale selection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[122]  B. S. Carlson,et al.  Comparison of modern CCD and CMOS image sensor technologies and systems for low resolution imaging , 2002, Proceedings of IEEE Sensors.

[123]  Sascha Spors,et al.  Joint audio-video object tracking , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[124]  Chengcui Zhang,et al.  Learning-based spatio-temporal vehicle tracking and indexing for transportation multimedia database systems , 2003, IEEE Trans. Intell. Transp. Syst..

[125]  Ramakant Nevatia,et al.  Tracking multiple humans in complex situations , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[126]  Michael Isard,et al.  BraMBLe: a Bayesian multiple-blob tracker , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[127]  Nir A. Sochen,et al.  Variational Stereo Vision with Sharp Discontinuities and Occlusion Handling , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[128]  Suchendra M. Bhandarkar,et al.  Multiple object tracking using elastic matching , 2005, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005..

[129]  Mubarak Shah,et al.  3D Model based Object Class Detection in An Arbitrary View , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[130]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[131]  W. Badawy,et al.  A real-time multiple target tracking algorithm using merged probabilistic data association technique and smoothing particle filter , 2006, 2006 IEEE Conference on Radar.

[132]  Yi Wu,et al.  Online Object Tracking: A Benchmark , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[133]  Azriel Rosenfeld,et al.  Sequential Operations in Digital Picture Processing , 1966, JACM.

[134]  Sheng-rong Gong,et al.  Adaptive Shadows Detection Algorithm Based on Gaussian Mixture Model , 2008, 2008 International Symposium on Information Science and Engineering.

[135]  Abdesselam Bouzerdoum,et al.  Detecting People in Images: An Edge Density Approach , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[136]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[137]  Murat Kunt,et al.  Spatiotemporal Segmentation Based on Region Merging , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[138]  Xin Li,et al.  Contour-based object tracking with occlusion handling in video acquired using mobile cameras , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[139]  Frank M. Candocia.  Simultaneous homographic and comparametric alignment of multiple exposure-adjusted pictures of the same scene , 2003, IEEE Trans. Image Process..

[140]  Sebastian Thrun,et al.  A Bayesian method for probable surface reconstruction and decimation , 2006, TOGS.

[141]  Yangsheng Xu,et al.  A detection system for human abnormal behavior , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[142]  Wayne H. Wolf,et al.  Multiple object tracking and occlusion handling by information exchange between uncalibrated cameras , 2005, IEEE International Conference on Image Processing 2005.

[143]  Ioannis Pitas,et al.  Digital image processing techniques for the detection and removal of cracks in digitized paintings , 2006, IEEE Transactions on Image Processing.

[144]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[145]  Silvio Savarese,et al.  3D generic object categorization, localization and pose estimation , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[146]  Mihai Datcu,et al.  Multiscale image segmentation with a dynamic label tree , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[147]  Yan Huang,et al.  Tracking multiple objects through occlusions , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[148]  Jenq-Neng Hwang,et al.  Tracking of multiple objects across multiple cameras with overlapping and non-overlapping views , 2009, 2009 IEEE International Symposium on Circuits and Systems.

[149]  Jean Meunier,et al.  Real-time video surveillance with self-organizing maps , 2005, The 2nd Canadian Conference on Computer and Robot Vision (CRV'05).

[150]  Keith Jack.  Digital Video and DSP: Instant Access , 2008 .

[151]  Nicolas Martel-Brisson,et al.  Moving cast shadow detection from a Gaussian mixture shadow model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[152]  David J. Kriegman,et al.  Synthetic Aperture Tracking: Tracking through Occlusions , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[153]  Cláudio Rosito Jung.  Multiscale image segmentation using wavelets and watersheds , 2003, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003).

[154]  David C. Hogg,et al.  Representation and synthesis of behaviour using Gaussian mixtures , 2002, Image Vis. Comput..

[155]  Yaakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking , 1995 .

[156]  Jae-Young Choi,et al.  Multiple Vehicles Detection and Tracking based on Scale-Invariant Feature Transform , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[157]  Jos B. T. M. Roerdink,et al.  The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.

[158]  Aggelos K. Katsaggelos,et al.  Abnormal Event Detection from Surveillance Video by Dynamic Hierarchical Clustering , 2007, 2007 IEEE International Conference on Image Processing.

[159]  Zehang Sun,et al.  Monocular precrash vehicle detection: features and classifiers , 2006, IEEE Transactions on Image Processing.

[160]  Ji Tao,et al.  Quickest change detection for health-care video surveillance , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[161]  Chung-Lin Huang,et al.  Abnormal Event Detection in Video Using N-cut Clustering , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[162]  Danica Kragic,et al.  Tracking techniques for visual servoing tasks , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[163]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[164]  Jesse S. Jin,et al.  Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces , 2004, VIP.

[165]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[166]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[167]  Fan Yang,et al.  A Tracking Model with Occlusion Handling Based on Information Fusion , 2007, 2007 10th IEEE International Conference on Computer-Aided Design and Computer Graphics.

[168]  Mubarak Shah,et al.  A non-iterative greedy algorithm for multi-frame point correspondence , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[169]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[170]  Camillo Gentile,et al.  Segmentation for robust tracking in the presence of severe occlusion , 2004, IEEE Trans. Image Process..

[171]  Pedro Pina,et al.  Crater Detection by a Boosting Approach , 2009, IEEE Geoscience and Remote Sensing Letters.

[172]  Daniel Snow,et al.  Pedestrian detection using boosted features over many frames , 2008, 2008 19th International Conference on Pattern Recognition.

[173]  Ming Yang,et al.  Multiple Collaborative Kernel Tracking , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[174]  Stanley T. Birchfield,et al.  Real-Time Incremental Segmentation and Tracking of Vehicles at Low Camera Angles Using Stable Features , 2008, IEEE Transactions on Intelligent Transportation Systems.

[175]  Rama Chellappa,et al.  Statistical shape theory for activity modeling , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[176]  Z. M. Hefed.  Object tracking , 1999 .

[177]  Shang-Hong Lai,et al.  Adaptive Foreground Object Extraction for Real-Time Video Surveillance with Lighting Variations , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[178]  Danica Kragic,et al.  Integration of Model-based and Model-free Cues for Visual Object Tracking in 3D , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[179]  Paulo Cortez,et al.  Prediction of Abnormal Behaviors for Intelligent Video Surveillance Systems , 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

[180]  Abdesselam Bouzerdoum,et al.  Skin segmentation using color pixel classification: analysis and comparison , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[181]  Larry D. Hostetler,et al.  The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.

[182]  Tieniu Tan,et al.  3-D model-based vehicle tracking , 2005, IEEE Transactions on Image Processing.

[183]  Gregory D. Hager,et al.  Probabilistic Data Association Methods for Tracking Complex Visual Objects , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[184]  Kok Kiong Tan,et al.  Neural network control : theory and applications , 2004 .

[185]  F. Ade,et al.  Tracking cars in range images using the CONDENSATION algorithm , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[186]  Yizong Cheng,et al.  Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[187]  Yogesh Rathi,et al.  Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow , 2007, IEEE Transactions on Image Processing.

[188]  A. Tannenbaum,et al.  Dynamic geodesic snakes for visual tracking , 2004, CVPR 2004.

[189]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[190]  Fernando Pérez-Cruz,et al.  Supervised-PCA and SVM classifiers for object detection in infrared images , 2003, Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003..

[191]  Yoav Freund,et al.  A Short Introduction to Boosting , 1999 .

[192]  Samy Bengio,et al.  Semi-supervised adapted HMMs for unusual event detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[193]  A. Bouzerdoum,et al.  VLSI Implementation of a Skin Detector Based on a Neural Network , 2005, 2005 5th International Conference on Information Communications & Signal Processing.

[194]  Djemel Ziou,et al.  Edge Detection Techniques-An Overview , 1998 .