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

N. Dalal, B. Triggs, and C. Schmid, Human Detection Using Oriented Histograms of Flow and Appearance, Europe Conf
DOI : 10.1023/A:1008162616689
URL : https://hal.archives-ouvertes.fr/inria-00548587

. Comp, Vision (ECCV), volume II, pp.428-441, 2006.

N. Dalal, Finding people in images and videos, 2006.
URL : https://hal.archives-ouvertes.fr/tel-00390303

J. Friedman, T. Hastie, and R. Tibshira, Additive logistic regression: a statistical view of boosting, Ann. Statist, vol.23, issue.2, pp.337-407, 2000.

. Fig, Detection examples. Green dots show all the detection results Red dots are final detection results via post-processing and the bounding boxes are average detection window sizes. [5] D. Gavrila and V. Philomin. Real-time object detection for " smart " vehicles, IEEE CVPR, pp.87-93, 1999.

M. Hussein, W. Abd-almageed, Y. Ran, and L. Davis, A real-time system for human detection, tracking and verification in uncontrolled camera motion environment, IEEE International Conference on Computer Vision Systems, 2006.

S. Ioffe and D. A. Forsyth, Probabilistic methods for finding people, Int. Journal of Comp. Vision, vol.43, issue.1, pp.46-68, 2001.

C. Mikolajczyk, B. Leibe, and B. Schiele, Multiple Object Class Detection with a Generative Model, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.26-36, 2006.
DOI : 10.1109/CVPR.2006.202

K. Mikolajczyk, C. Schmid, and A. Zisserman, Human Detection Based on a Probabilistic Assembly of Robust Part Detectors, Europe Conf. Comp. Vision (ECCV), volume I, pp.69-81, 2004.
DOI : 10.1007/978-3-540-24670-1_6
URL : https://hal.archives-ouvertes.fr/inria-00548537

S. Munder and D. M. Gavrila, An Experimental Study on Pedestrian Classification, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.11, pp.1863-1868, 2006.
DOI : 10.1109/TPAMI.2006.217

P. Papageorgiou and T. Poggio, A trainable system for object detection, International Journal of Computer Vision, vol.38, issue.1, pp.15-33, 2000.
DOI : 10.1023/A:1008162616689

X. Pennec, P. Fillard, and N. Ayache, A Riemannian Framework for Tensor Computing, International Journal of Computer Vision, vol.6, issue.2, pp.41-66, 2006.
DOI : 10.1007/s11263-005-3222-z
URL : https://hal.archives-ouvertes.fr/inria-00070743

E. Seemann, M. Fritz, and B. Schiele, Towards Robust Pedestrian Detection in Crowded Image Sequences, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383300

O. Tuzel, F. M. Porikli, and P. Meer, Region Covariance: A Fast Descriptor for Detection and Classification, Europe Conf. Comp. Vision (ECCV), volume II, pp.589-600, 2006.
DOI : 10.1023/B:VISI.0000029664.99615.94

O. Tuzel, F. Porikli, and P. Meer, Human Detection via Classification on Riemannian Manifolds, 2007 IEEE Conference on Computer Vision and Pattern Recognition
DOI : 10.1109/CVPR.2007.383197

P. Viola, M. J. Jones, and D. Snow, Detecting Pedestrians Using Patterns of Motion and Appearance, International Journal of Computer Vision, vol.20, issue.3, pp.153-161, 2005.
DOI : 10.1007/s11263-005-6644-8

J. Yao and J. Odobez, Multi-Layer Background Subtraction Based on Color and Texture, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383497
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.585