T. Vu, Vehicle Perception : Localization , Mapping with Detection , Classification and Tracking of Moving Objects, 2009.
URL : https://hal.archives-ouvertes.fr/tel-00454238

Q. Baig, Multisensor Data Fusion for Detection and Tracking of Moving Objects From a Dynamic Autonomous Vehicle, 2012.

C. Wang, C. Thorpe, S. Thrun, M. Hebert, and H. Durrant-whyte, Simultaneous Localization, Mapping and Moving Object Tracking, The International Journal of Robotics Research, vol.26, issue.9, pp.889-916, 2007.
DOI : 10.1177/0278364907081229

C. Mertz, L. E. Navarro-serment, R. Maclachlan, P. Rybski, A. Steinfeld et al., Moving object detection with laser scanners, Journal of Field Robotics, vol.30, issue.9, pp.17-43, 2013.
DOI : 10.1002/rob.21430

F. Fayad and V. Cherfaoui, Detection and Recognition confidences update in a multi-sensor pedestrian tracking system, Information Processing and Management of Uncertainty in Knowledge- Based Systems, pp.409-416, 2008.

M. Perrollaz, C. Roy, N. Hauti, and D. Aubert, Long Range Obstacle Detection Using Laser Scanner and Stereovision, 2006 IEEE Intelligent Vehicles Symposium, pp.182-187, 2006.
DOI : 10.1109/IVS.2006.1689625

URL : https://hal.archives-ouvertes.fr/hal-00671213

R. Labayrade, D. Gruyer, C. Royere, M. Perrollaz, and D. Aubert, Obstacle Detection Based on Fusion Between Stereovision and 2D Laser Scanner, Mobile Robots: Perception & Navigation, 2007.
DOI : 10.5772/4769

URL : https://hal.archives-ouvertes.fr/hal-00683758

M. Skutek, D. Linzmeier, N. Appenrodt, and G. Wanielik, A precrash system based on sensor data fusion of laser scanner and short range radars, 2005 7th International Conference on Information Fusion, p.8, 2005.
DOI : 10.1109/ICIF.2005.1592005

R. Chavez-garcia, T. Vu, O. Aycard, and F. Tango, Fusion framework for moving-object classification, Information Fusion, 2013 16th International Conference on, pp.1159-1166, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00881147

P. Smets, Data fusion in the transferable belief model, Proceedings of the Third International Conference on Information Fusion, pp.21-33, 2000.
DOI : 10.1109/IFIC.2000.862713

R. R. Yager, ON THE RELATIONSHIP OF METHODS OF AGGREGATING EVIDENCE IN EXPERT SYSTEMS, Cybernetics and Systems, vol.10, issue.1, pp.1-21, 1985.
DOI : 10.1080/01969728508927754

R. Chavez-garcia, T. D. Vu, and O. Aycard, Fusion at detection level for frontal object perception, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.1225-1230, 2014.
DOI : 10.1109/IVS.2014.6856555

URL : https://hal.archives-ouvertes.fr/hal-01010374

P. Dollár, C. Wojek, B. Schiele, and P. Perona, Pedestrian detection: an evaluation of the state of the art Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.4, pp.743-61, 2012.

P. Viola and M. Jones, Robust real-time object detection, Cambridge Research Laboratory, 2001.

J. Friedman, T. Hastie, and R. Tibshirani, Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors), The Annals of Statistics, vol.28, issue.2, pp.337-655, 2000.
DOI : 10.1214/aos/1016218223

J. Civera, A. J. Davison, and J. M. , Interacting multiple model monocular SLAM, 2008 IEEE International Conference on Robotics and Automation, pp.3704-3709, 2008.
DOI : 10.1109/ROBOT.2008.4543779

K. Dietmayer, J. Sparbert, and D. Streller, Model Based Object Classification and Tracking in Traffic Scenes from Range Images, IEEE Intelligent Vehicle Symposium, 2001.