J. K. Aggarwal and Q. Cai, Human motion analysis: a review, The Nonrigid and Articulated Motion Workshop, pp.90-102, 1997.

D. L. Almanza-ojeda, Détection et suivi d'objets mobiles perçus depuis un capteur visuel embarqué, 2011.

A. Almeida, J. Almeida, and R. Araujo, Real-time tracking of multiple moving objects using particle filters and probabilistic data association, Automatika, pp.39-48, 2005.

P. Baiget, E. Sommerlade, I. Reid, and J. Gonzalez, Finding Prototypes to Estimate Trajectory Development in Outdoor Scenarios, The 1st International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences (THEMIS), in conjunction with The British Machine Vison Conference (BMVC), 2009.

S. Bak, E. Corvee, F. Bremond, and M. Thonnat, Person Re-indentification using Haar-based and DCD-based Signature, The 2nd Workshop on Activity Monitoring by Multi- Camera Surveillance Systems (AMMCSS), in conjunction with The International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2010.

D. Beymer and K. Konolige, Real-time tracking of multiple people using continuous detection, The Frame-Rate Workshop, in conjunction with The IEEE International Conference on Computer Vision (ICCV), 1999.

P. Bilinski, F. Bremond, and M. Kaaniche, Multiple object tracking with occlusions using HOG descriptors and multi resolution images, 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP 2009), 2009.
DOI : 10.1049/ic.2009.0264

URL : https://hal.archives-ouvertes.fr/inria-00510410

T. Broida and R. Chellappa, Estimation of Object Motion Parameters from Noisy Images, The IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.90-99, 1986.
DOI : 10.1109/TPAMI.1986.4767755

D. P. Chau, F. Bremond, and M. Thonnat, A multifeature tracking algorithm enabling adaptation to context variations Robust mobile object tracking based on multiple feature similarity and trajectory filtering, The International Conference on Imaging for Crime Detection and Prevention The International Conference on Computer Vision Theory and Applications (VISAPP), 2011.

A. Colombo, J. Orwell, and S. Velastin, Color Constancy Techniques for Re-Recognition of Pedestrians from Multiple Surveillance Cameras, Workshop on Multicamera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008.

D. Comaniciu and P. Meer, Robust analysis of feature spaces: color image segmentation, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.750-755, 1997.
DOI : 10.1109/CVPR.1997.609410

E. Corvee and F. Bremond, Combining face detection and people tracking in video surveillance, The International Conference on Imaging for Crime Detection and Prevention (ICDP), 2009.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

C. E. Erdem, M. Tekalp, and B. Sankur, Video object tracking with feedback of performance measures, The IEEE Transactions on Circuits and Systems for Video Technology, pp.310-324, 2003.
DOI : 10.1109/TCSVT.2003.811361

Y. Freund and R. E. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, The Journal of Computer and System Sciences, pp.522-536, 1997.
DOI : 10.1006/jcss.1997.1504

H. Grabner and H. Bischof, Online Boosting and Vision, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.260-267, 2006.

R. Johnson, Tutorial: A Brief Summarization of the Kalman Filter, 1998.

J. Kang, I. Cohen, and G. Medioni, Object Reacquisition Using Invariant Appearance Model, The International Conference on Pattern Recognition (ICPR), 2004.

C. Kuo, C. Huang, and R. Nevatia, Multi-target tracking by online learned discriminative appearance models, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.

E. Monari, J. Maerker, and K. Kroschel, A Robust and Efficient Approach for Human Tracking in Multi-camera Systems, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009.
DOI : 10.1109/AVSS.2009.16

C. Motamed, Motion detection and tracking using belief indicators for an automatic visualsurveillance system, The Journal of Image and Vision Computing, pp.1192-1201, 2006.

T. Ojala, M. Pietikainen, and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, The IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.971-987, 2002.
DOI : 10.1109/TPAMI.2002.1017623

K. Robert, Night-Time Traffic Surveillance: A Robust Framework for Multi-vehicle Detection, Classification and Tracking, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009.
DOI : 10.1109/AVSS.2009.98

E. Rosten and T. Drummond, Machine learning for highspeed corner detection, The European Conference on Computer Vision (ECCV), 2006.

Y. Rubner, C. Tomasi, and L. Guibas, A metric for distributions with applications to image databases, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 1998.
DOI : 10.1109/ICCV.1998.710701

P. Scovanner and M. Tappen, Learning pedestrian dynamics from the real world, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459224

L. Snidaro, I. Visentini, and G. Foresti, Dynamic Models for People Detection and Tracking, 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, pp.29-35, 2008.
DOI : 10.1109/AVSS.2008.29

S. Torkan and A. Behrad, A new contour based tracking algorithm using improved greedy snake, 2010 18th Iranian Conference on Electrical Engineering, 2010.
DOI : 10.1109/IRANIANCEE.2010.5507085

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.511-518, 2003.
DOI : 10.1109/CVPR.2001.990517

N. Xu and N. Ahuja, Object contour tracking using graph cuts based active contours, Proceedings. International Conference on Image Processing, 2002.
DOI : 10.1109/ICIP.2002.1038959

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.389.4167

A. Yilmaz, O. Javed, and M. Shah, Object tracking, ACM Computing Surveys, vol.38, issue.4, 2006.
DOI : 10.1145/1177352.1177355

A. Yilmaz and M. Shah, Contour-based object tracking with occlusion handling in video acquired using mobile cameras, The IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004.
DOI : 10.1109/TPAMI.2004.96

Y. Zhou, B. Hu, and J. Zhang, Occlusion Detection and Tracking Method Based on Bayesian Decision Theory, The Lecture Notes in Computer Science, pp.474-482, 2006.
DOI : 10.1007/11949534_47