. Finally, the level of risk and the direction of the risk are sent to the Human Machine Interface (HMI) inside the bus to warn the bus driver

Y. Abramson, B. Steux, and H. Ghorayeb, Yef real-time object detection, ALART'05:International workshop on Automatic Learning and Real-Time, pp.5-13, 2005.

J. Bobruk and D. Austin, Laser motion detection and hypothesis tracking from a mobile platform, Australasian Conference on Robotics and Automation (ACRA), 2004.

J. Black, T. Ellis, and P. Rosin, A novel method for video tracking performance evaluation, International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp.125-132, 2003.

]. I. Bfh04a, K. Buck, and H. Fatahalian, Gpubench: Evaluating gpu performance for numerical and scientific applications, Proceedings of the 2004 ACM Workshop on General-Purpose Computing on Graphics Processors, 2004.

]. I. Bfh-+-04b, T. Buck, D. Foley, J. Horn, K. Sugerman et al., Brook for gpus: Stream computing on graphics hardware, 2004.

R. [. Boult, X. Micheals, M. Gao, and . Eckmann, Into the woods: visual surveillance of noncooperative and camouflaged targets in complex outdoor settings, Proceedings of the IEEE, vol.89, issue.10, 2001.
DOI : 10.1109/5.959337

H. Ghorayeb, B. Steux, and Y. Abramson, Camellia image processing library, 2003.

C. Stauffer and W. E. Grimson, Adaptive background mixture models for real-time tracking, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.747-757, 0193.
DOI : 10.1109/CVPR.1999.784637

B. Chen and Y. Lei, Indoor and outdoor people detection and shadow suppression by exploiting hsv color information. cit, pp.137-142, 2004.

F. C. Crow, Summed-area tables for texture mapping, SIGGRAPH '84: Proceedings of the 11th annual conference on Computer graphics and interactive techniques, pp.207-212, 1984.

U. [. Cramer, G. Scheunert, and . Wanielik, Multi sensor fusion for object detection using generalized feature models, Sixth International Conference of Information Fusion, 2003. Proceedings of the, 2003.
DOI : 10.1109/ICIF.2003.177419

Y. Dedeoglu, Moving object detection, tracking and classification for smart video surveillance, 2004.

D. Doermann and D. Mihalcik, Tools and techniques for video performance evaluation, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.4167-4170, 2000.
DOI : 10.1109/ICPR.2000.902888

R. [. Drucker, P. Schapire, and . Simard, BOOSTING PERFORMANCE IN NEURAL NETWORKS, International Journal of Pattern Recognition and Artificial Intelligence, vol.07, issue.04, pp.705-719, 1993.
DOI : 10.1142/S0218001493000352

A. Elfes, Using occupancy grids for mobile robot perception and navigation, Computer, vol.22, issue.6, pp.46-57, 1989.
DOI : 10.1109/2.30720

M. Ekman, F. Warg, and J. Nilsson, An in-depth look at computer performance growth, ACM SIGARCH Computer Architecture News, vol.33, issue.1, 2004.
DOI : 10.1145/1055626.1055646

J. P. Farrugia and P. Horain, GPUCV: A Framework for Image Processing Acceleration with Graphics Processors, 2006 IEEE International Conference on Multimedia and Expo, 2006.
DOI : 10.1109/ICME.2006.262476

J. Fung and S. Mann, OpenVIDIA, Proceedings of the 13th annual ACM international conference on Multimedia , MULTIMEDIA '05, pp.849-852, 2005.
DOI : 10.1145/1101149.1101334

]. Y. Fre90, Y. Freund, R. E. Freund, and . Schapire, Boosting a weak learning algorithm by majority A decision-theoretic generalization of on-line learning and an application to boosting, Proceedings of the Third Annual Workshop on Computational Learning Theory European Conference on Computational Learning Theory, pp.202-216, 1990.

Y. Freund and R. E. Schapire, A decision-theoretic generalization of online learning and an application to boosting, Computational Learning Theory: Second European Conference, EuroCOLT '95, pp.23-37

Y. Freund and R. E. Schapire, A short introduction to boosting, Journal of Japanese Society for Artificial Intelligence, vol.14, issue.5, pp.771-780, 1999.

D. Hall, Comparison of target detection algorithms using adaptive background models. INRIA Rhone-Alpes, pp.585-601, 2005.

]. A. Hbc-+-03, L. Hampapur, J. Brown, S. Connell, A. Pankanti et al., Smart surveillance: Applications, technologies and implications, 2003.

H. Ghorayeb, B. Steux, and C. Laurgeau, Boosted Algorithms for Visual Object Detection on Graphics Processing Units, ACCV06: Asian Conference on Computer Vision, pp.254-263, 2006.
DOI : 10.1007/11612704_26

F. Heijden, Image Based Measurement Systems: Object Recognition and Parameter Estimation, 1996.

P. Perez, C. Hue, J. Vermaak, and M. Gangnet, Color-Based Probabilistic Tracking, IEEE Transactions on multimedia, 2002.
DOI : 10.1007/3-540-47969-4_44
URL : https://hal.archives-ouvertes.fr/inria-00285122

J. Staufer, R. Mech, and J. Ostermann, Detection of moving cast shadows for object segmentation, IEEE Transactions on multimedia, pp.65-76, 1999.

S. [. Jaynes, R. Webb, Q. Steele, and . Xiong, An open development environment for evaluation of video surveillance systems, 2002.

. Kenji, A boosted particle filter multi?target detection and tracking. ICCV, 2004.

E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, vol.82, issue.1, pp.35-45, 1960.
DOI : 10.1115/1.3662552

M. Kais, S. Dauvillier, A. De-la-fortelle, I. Masaki, and C. Laugier, Towards outdoor localization using gis, vision system and stochastic error propagation, International Conference on Autonomous Robots and Agents, 2004.

F. [. Khammari, Y. Nashashibi, C. Abramson, and . Laurgeau, Vehicle detection combining gradient analysis and adaboost classification, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005., pp.66-71, 2005.
DOI : 10.1109/ITSC.2005.1520202

M. Kearns and L. G. Valiant, Learning boolean formula or finite automate is as hard as factoring, 1988.

M. Kearns and L. G. Valiant, Cryptographic limitations on learning boolean formula and finite automate, Proceedings of the Twenty First Annual ACM Symposium on Theory of Computing, pp.433-444, 1989.

J. Michael, U. V. Kearns, and . Vazirani, An Introduction to Computational Learning Theory, 1994.

. Ops-+-97-]-m, C. Oren, P. Papageorgiou, E. Sinha, T. Osuna et al., Pedestrian detection using wavelet templates, Proc. Computer Vision and Pattern Recognition, pp.193-199, 1997.

T. Parag, A. Elgammal, and A. Mittal, A Framework for Feature Selection for Background Subtraction, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.1916-1923, 2006.
DOI : 10.1109/CVPR.2006.24

T. [. Rosin and . Ellis, Image Difference Threshold Strategies and Shadow Detection., Procedings of the British Machine Vision Conference 1995, pp.347-356, 1995.
DOI : 10.5244/C.9.35

M. Rochery, R. Schapire, M. Rahim, N. Gupta, G. Riccardi et al., Combining prior knowledge and boosting for call classification in spoken language dialogue, IEEE International Conference on Acoustics Speech and Signal Processing, 2002.
DOI : 10.1109/ICASSP.2002.5743646

B. Steux, Y. Abramson, and H. Ghorayeb, Initial algorithms 1, delivrable 3.2b, project ist-2001-34410, public report, References [SAG03b] B. Steux, Y. Abramson, and H. Ghorayeb. Report on mapped algorithms, pp.2001-34410, 2003.

]. R. Sch89 and . Schapire, The strength of weak learnability, 30th Annual Symposium on Foundations of Computer Science, pp.28-33, 1989.

R. Strzodka, M. Doggett, and A. Kolb, Scientific computation for simulations on programmable graphics hardware. Simulation Modelling Practice and Theory, Special Issue: Programmable Graphics Hardware, pp.667-680, 2005.

J. Steffens, E. Elagin, and H. Neven, Person spotter-fast and robust system for human detection, Proc. of IEEE Intl. Conf. on Automatic Face and Gesture Recognition, pp.516-521, 1998.

R. E. Schapire and Y. Singer, Improved boosting algorithms using confidence-rated predictions, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, pp.80-91, 1998.
DOI : 10.1145/279943.279960

T. Horprasert, D. Harwood, and L. S. Davis, A statistical approach for real-time robust background subtraction and shadow detection, Proceedings of International Conference on computer vision, 1999.

J. [. Toyama, B. Krumm, B. Brumitt, and . Meyers, Wallflower: principles and practice of background maintenance, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.255-261, 1999.
DOI : 10.1109/ICCV.1999.791228

L. G. Valiant, A theory of the learnable, Communications of the ACM, vol.27, issue.11, pp.1134-1142, 1984.
DOI : 10.1145/1968.1972

]. P. Vj01a, M. Viola, and . Jones, Rapid object detection using a boosted cascade of simple features, European Conference on Computational Learning Theory, 2001.

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, 2001.
DOI : 10.1109/CVPR.2001.990517

J. [. Marianoand, J. Min, R. Park, and . Kasturi, Performance evaluation of object detection algorithms, International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp.965-969, 2002.

P. Viola, M. J. Jones, and D. Snow, Detecting pedestrians using patterns of motion and appearance, IEEE International Conference on Computer Vision, pp.734-741, 2003.

A. [. Wren, T. Azarbayejani, A. Darrell, and . Pentland, Pfinder: real-time tracking of the human body, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.7, pp.780-785, 1997.
DOI : 10.1109/34.598236

L. Wang, W. Hu, and T. Tan, Recent developments in human motion analysis, Proceedings IEEE Conf. on Computer Vision and Pattern Recognition, p.585601, 2003.
DOI : 10.1016/S0031-3203(02)00100-0

L. Wang, W. Hu, and T. Tan, Recent developments in human motion analysis, Pattern Recognition, vol.36, issue.3, pp.585-601, 2003.
DOI : 10.1016/S0031-3203(02)00100-0

M. Yguel, O. Aycard, D. Raulo, and C. Laugier, Grid based fusion of offboard cameras, IEEE International Conference on Intelligent Vehicules, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00182016

W. [. Zhang, X. Jia, Q. He, and . Wu, Learning-based license plate detection using global and local features, Pattern Recognition 18th International Conference on, pp.1102-1105, 2006.