.. Suivi-des-détections-lidar, 68 3.3.6 Construction des zones d'intérêt, p.69

.. Algorithme-de-traitement-du-récepteur, 72 3.4.3 Construction des zones d'intérêt, p.77

.. Modèle-d-'évolution-des-objets-détectés, 97 4.4.4 Observation et association, p.98

?. A. Von-arnim, M. Perrollaz, A. Bertrand, and &. J. Ehrlich, Vehicle Identification Using Infrared Vision and Applications to Cooperative Perception, IEEE Intelligent Vehicles Symposium, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00364713

?. R. Chapitre-d-'ouvrage, D. Labayrade, C. Gruyer, &. M. Royère, and . Perrollaz, Obstacle Detection in Outdoor Environments Based on Fusion Between Stereovision and Laser Scanner. (Chapitre 7 de "Moving Robots, Moving Intelligence, Novembre 2006. Coordonné par l'éditeur en chef de : International Journal of Advanced Robotic Systems

?. A. Brevet, M. Von-arnim, &. J. Perrollaz, and V. Naranjo, Chevreau : « Système et procédé de communication et d'identification intervehiculaire », Brevet Français déposé le 15 Janvier Automatic license plate reading using mathematical morphology, Proceedings of the VIIP Conference, 2004.

F. R. Aufrère, R. Marmoiton, F. Chapuis, J. P. Collange, and . Dérutin, Detection de route et suivi de véhicules par vision pour l'acc, Traitement du Signal, vol.17, issue.3, pp.233-248, 2000.

S. Ammoun, M. Bertozzi, and A. Broggi, Contribution des communications intervéhiculaires pour la conception de systèmes avancés d'aide à la conduite Ecole des mines de Paris, Decembre Gold : A parallel real-time stereo vision system for generic obstacle and lane detecion, IEEE Transactions on Image Processing, vol.7, issue.1, 1998.

M. Bertozzi, A. Broggi, A. Fascioli, and S. Nichele, Stereo vision-based vehicle detection, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511), 2000.
DOI : 10.1109/IVS.2000.898315

URL : https://hal.archives-ouvertes.fr/hal-00478467

M. Bertozzi, A. Broggi, A. Lasagni, and M. D. Rose, Infrared stereo vision-based pedestrian detection, IEEE Proceedings. Intelligent Vehicles Symposium, 2005., 2005.
DOI : 10.1109/IVS.2005.1505072

. Bbm-+-06-]-m, A. Bertozzi, P. Broggi, P. P. Medici, A. Porta et al., Stereo vision-based start-inhibit for heavy goods vehicles, Proceedings of the IEEE Intelligent Vehicles Symposium, 2006.

A. Broggi, C. Caraffi, P. P. Porta, and P. Zani, The Single Frame Stereo Vision System for Reliable Obstacle Detection Used during the 2005 DARPA Grand Challenge on TerraMax, 2006 IEEE Intelligent Transportation Systems Conference, 2006.
DOI : 10.1109/ITSC.2006.1706831

A. Broggi, S. Cattani, P. P. Porta, P. Zani, A. Broggi et al., A laserscanner-vision fusion system implemented on the terramax autonomous vehicle Pedestrian detection on a moving vehicle : an investigation about near infra-red images Highway scene analysis in hard real-time Highway scene analysis form a moving vehicle under reduced visibility conditions, Proceedings of the International Conference on Intelligent Robots and Systems Proceedings of the IEEE Intelligent Vehicles Symposium Proceedings of the IEEE Conference on Intelligent Transportation Systems Proceedings of the IEEE International Conference on Intelligent Vehicles, 1997.

R. [. Blackman and . Popoli, Design and analysis of modern tracking systems, 1999.

C. [. Birchfield and . Tomasi, A pixel dissimilarity measure that is insensitive to image sampling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.4, pp.401-406, 1998.
DOI : 10.1109/34.677269

T. [. Bay, L. Tuytelaars, and . Van-gool, Surf : Speeded up robust features, Proceedings of the 9th European Conference on Computer Vision, 2006.
DOI : 10.1007/11744023_32

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.3046

]. S. Cha05 and . Chambon, Mise en correspondance stéréoscopique d'images couleur en présence d'occultations, III, 2005. [col05] Ouvrage collectif. Sur la route... la sécurité Les collections de l'INRETS. IN- RETS, 2005.

]. F. Dev97 and . Devernay, Vision stéréoscopique et propriétés differentielles des surfaces, 1997.

J. Douret, R. Labayrade, J. Laneurit, and R. Chapuis, A reliable and robust lane detection system based on the parallel use of three algorithms for driving safety assistance, IAPR Conference on Machine Vision and Applications, 2005.

R. [. Egnal and . Wildes, Detecting binocular half-occlusions: empirical comparisons of five approaches, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.8, pp.1127-1133, 2002.
DOI : 10.1109/TPAMI.2002.1023808

]. J. Fab04 and . Fabrizio, Localisation d'obstacles cooperatifs par systèmes de vision classiques et panoramiques, 2004.

. Fdw-+-06-]-b, J. Fardi, G. Dousa, B. Wanielik, A. Elias et al., Obstacle detection and pedestrian recognition using a 3d pmd camera, Proceedings of the IEEE Intelligent Vehicles Symposium, 2006.

A. [. Franke and . Joos, Real-time stereo vision for urban traffic scene understanding, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511), 2000.
DOI : 10.1109/IVS.2000.898354

B. Fremont, A. Menhaj, P. Deloof, and M. Heddebaut, A cooperative collision avoidance and communication system for railway transports, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493), 2000.
DOI : 10.1109/ITSC.2000.881055

V. [. Fusiello, E. Roberto, and . Trucco, Efficient stereo with multiple windowing, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.858-863, 1997.
DOI : 10.1109/CVPR.1997.609428

E. [. Fusiello, A. Trucco, and . Verri, A compact algorithm for rectification of stereo pairs. Machine Vision and Applications, pp.16-22, 2000.

W. [. Graefe and . Efenberger, A novel approach for the detection of vehicles on freeways by real-time vision, Proceedings of Conference on Intelligent Vehicles, 1996.
DOI : 10.1109/IVS.1996.566407

]. P. Glm-+-01, D. Griffiths, J. A. Langer, M. Misener, C. Siegel et al., Sensor-friendly vehicle and roadway systems, Proceedings of the IEEE Instrumentation and Measurement Technology Conference, 2001.

V. [. Gavrila and . Philomin, Real-time objet detection for "smart" vehicles, Proceedings of the IEEE International Conference on Computer Vision, pp.87-93, 1999.
DOI : 10.1109/iccv.1999.791202

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.3059

]. D. Gru99 and . Gruyer, Etude du Traitement de données imparfaites pour le suivi multi-objets : Application aux situations routières, 1999.

D. Geronimi, A. D. Sappa, A. Lopez, and D. Ponsa, Adaptive image sampling and windows classification for on-board pedestrian detection, Proceedings of the 5th International Conference on Computer Vision Systems, 2007.

E. [. Gerbenne, R. Tournie, C. Artur, and . Narduzzi, Arcos 2004 -analyse fonctionnelle, 2002.

]. J. Han99 and . Hancock, Laser Intensity-Based Obstacle Detection and Tracking, 1999.

P. [. Hirschmüller, J. M. Innocent, and . Garibaldi, Real-time correlation-based stereo vision with reduced border errors, International Journal of Computer Vision, vol.47, pp.1-3229, 2002.

R. [. Hautière, M. Labayrade, D. Perrollaz, and . Aubert, Road Scene Analysis by Stereovision: a Robust and Quasi-Dense Approach, 2006 9th International Conference on Control, Automation, Robotics and Vision, 2006.
DOI : 10.1109/ICARCV.2006.345163

O. [. Horaud and . Monga, Vision par ordinateur : Outils fondamentaux, Hermes, 1995.
URL : https://hal.archives-ouvertes.fr/inria-00590049

]. P. Hou62 and . Hough, A method and means for recognizing complex patterns, U.S. Patent No, vol.3, p.69654, 1962.

A. [. Hartley and . Zisserman, Multiple View Geometry in Computer Vision (second edition), 2003.

C. [. Itti, E. Koch, and . Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.11, pp.1254-1259, 1998.
DOI : 10.1109/34.730558

M. [. Kaempchen, K. Buehler, and . Dietmayer, Feature-level fusion for free-form object tracking using laserscanner and video, IEEE Proceedings. Intelligent Vehicles Symposium, 2005., 2005.
DOI : 10.1109/IVS.2005.1505145

. Kko-+-06-]-y, T. Kimura, M. Kato, Y. Ohta, Y. Ninomiya et al., Stereovision for obstacle detection, Proceedings of the 13th World Congress on Intelligent Transportation Systems, 2006.

M. [. Kanade and . Okutomi, A stereo matching algorithm with an adaptive window: theory and experiment, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.16, issue.9, pp.920-932, 1994.
DOI : 10.1109/34.310690

]. K. Kon97 and . Konolige, Small vision system : Hardware and implementation, Proceedings of the 8th International Symposium on Robotics Research, 1997.

]. R. La03a, D. Labayrade, . Aubertla03b-]-r, D. Labayrade, and . Aubert, A single framework for vehicle roll, pitch, yaw estimation and obstacles detection by stereovision Robuste et Rapide d'obstacles Routiers par Stéréovision Embarquée, Proceedings of the 1st International Workshop on In-Vehicle Cognitive Computer Vision Systems Proceedings of the IEEE Intelligent Vehicles SymposiumLAC06] S. Lefevbre, S. Ambellouis, and F. Cabestaing. Obstacle detection on a road by dense stereovision with 1d correlation windows and fuzzy filtering Proceedings of the IEEE Conference on Intelligent Transportation Systems, 2003.

V. Lemonde, Détection d'obstacles par stéréovision sur véhicules intelligents, Proceedings des 9èmes journés Jeunes Chercheurs en Vision par Ordinateur (ORASIS 05), 2005.

V. Lemonde, D. S. Lowe-[-lp03-]-h, G. Liu, and . Pang, Distinctive image features from scale-invariant keypoints Positioning beacon system using digital camera and leds Match propagation for image-based modeling and rendering, Mars 2003. [LQ02] M. Lhuillier and L. QuanLRA05] R. Labayrade, C. Royère, and D. Aubert. A collision mitigation system using laser scanner and stereovision fusion and its assesment Proceedings of the IEEE Intelligent Vehicles Symposium, pp.91-1101140, 2002.

R. Labayrade, C. Royere, D. Gruyer, and D. Aubert, Cooperative Fusion for Multi-Obstacles Detection With Use of Stereovision and Laser Scanner, Proceedings of the Conference on Computer Vision and Pattern Recognition, pp.117-140, 1999.
DOI : 10.1007/s10514-005-0611-7

A. Mendes, L. C. Bento, and U. Nunes, Multi-target detection and tracking with a laserscanner A study on the safety-capacity tradeoff improvement by warning communications, Proceedings of the IEEE Intelligent Vehicles Symposium Proceedings of the IEEE Conference on Intelligent Transportation Systems, 2004.

. Mgs-+-07-]-t, A. Michalke, M. Gepperth, J. Schneider, C. Fritsch et al., Towards a human-like vision system for resource-constrained intelligent cars, Proceedings of the 5th International Conference on Computer Vision SystemsMor77] H. Moravec. Toward automatic visual obstacle avoidance Proceedings of the 5th International Joint Conference on Artificial Intelligence, pp.584-590, 1977.

. [. Miled-souid, Mise en correspondance stéréoscopique par approches variationelles convexes ; Application à la détection d'obstacles routiers, 2007.

S. Nedevschi, R. Danescu, D. Frentiu, T. Marita, F. Oniga et al., High accuracy stereovision approach for obstacle detection on non planar roads, Proceedings of the IEEE Intelligent Engineering Systems, 2004.

S. Nedevschi, F. Oniga, R. Danescu, T. Graf, and R. Schmidt, Increased Accuracy Stereo Approach for 3D Lane Detection, 2006 IEEE Intelligent Vehicles Symposium, 2006.
DOI : 10.1109/IVS.2006.1689603

]. C. Roy02 and . Royère, Contribution à la résolution du conflit dans le cadre de la théorie de l'évidence. Application à la perception et à la localisation des véhicules intelligents, 2002.

J. [. Schreier, M. A. Braasch, and . Sutton, Systematic errors in digital image correlation caused by intensity interpolation, Optical Engineering, vol.39, issue.11, pp.392915-2921, 2000.
DOI : 10.1117/1.1314593

]. C. Sha49 and . Shannon, Communication in the presence of noise, Proceedings of the Institute of Radio Engineers, pp.10-21, 1949.

B. Steux, C. Laurgeau, L. Salesse, D. Wautier-stein, O. Mano et al., Fade : A véhicle detection and tracking system featuring monocular color vision and radar data fusion A robust method for computing vehicle egomotion, Proceedings of the IEEE Intelligent Vehicles Symposium Proceedings of the IEEE Intelligent Vehicles Symposium, 2000.

M. Skutek, M. Mekhaiel, and G. Wanielik, A precrash system based on radar for automotive applications, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683), 2003.
DOI : 10.1109/IVS.2003.1212879

M. [. Shimizu and . Okutomi, Precise sub-pixel estimation on area-based matching, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.90-97, 2001.
DOI : 10.1109/ICCV.2001.937503

M. [. Soquet, R. Perrollaz, D. Labayrade, and . Aubert, Free space estimation for autonomous navigation, Proceedings of the 5th International Conference on Computer Vision Systems, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00359200

F. Suard, A. Rakotomamonjy, A. Bensrhair, and A. Broggi, Pedestrian Detection using Infrared images and Histograms of Oriented Gradients, 2006 IEEE Intelligent Vehicles Symposium, 2006.
DOI : 10.1109/IVS.2006.1689629

]. D. Ss02a, R. Scharstein, and . Szeliski, A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, International Journal of Computer Vision, vol.47, issue.1-3, pp.7-42, 2002.

]. R. Ss02b, D. Szeliski, H. Scharstein, S. Takahashi, H. Sugimoto et al., Symmetric sub-pixel stereo matching Obstacle detection using millimeter-wave radar and its visualization on image sequence, Proceedings of the 7th European Conference on Computer Vision Proceedings of the International Conference on Pattern Recognition, pp.525-540, 2002.

]. B. Ste01 and . Steux, RTMaps, un environnement logiciel dédié à la conception d'applications embarquées temps-réel. Utilisation pour la détection automatique par fusion radar / vision, 2001.

. Tbm-+-06-]-g, M. Toulminet, S. Bertozzi, A. Mousset, A. Bensrhair et al., Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis, IEEE Transactions on Image Processing, vol.15, issue.8, pp.2364-2375, 2006.

H. [. Takada, O. Fujii, and . Hayashi, Multiple vehicle identification in a longitudinal ranging system, Proceedings of the World Congress on Intelligent Transportation Systems, 1997.

R. [. Talukder, A. Manduchi, L. Rankin, and . Matthies, Fast and reliable obstacle detection and segmentation for cross-country navigation, Intelligent Vehicle Symposium, 2002. IEEE, 2002.
DOI : 10.1109/IVS.2002.1188019

]. A. Von-arnim, M. Perrollaz, A. Bertrand, and J. Ehrlich, Vehicle identification using infrared vision and applications to cooperative perception, Proceedings of the IEEE Intelligent Vehicles Symposium, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00364713

]. W. Van-der-mark and D. M. Gavrila, Real-Time Dense Stereo for Intelligent Vehicles, IEEE Transactions on Intelligent Transportation Systems, vol.7, issue.1, pp.38-50, 2006.
DOI : 10.1109/TITS.2006.869625

]. O. Vek02 and . Veksler, Stereo correspondence with compact windows via minimum ratio cycle, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.12, pp.1654-1660, 2002.

]. T. Wil98 and . Williamson, A High-Performance Stereo Vision System for Obstacle Detection, 1998.

I. [. Yoon and . Kweon, Locally adaptative support-weight approach for visual correspondence search, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.924-931, 2005.

T. [. Yamaguchi, Y. Kato, and . Ninomiya, Moving Obstacle Detection using Monocular Vision, 2006 IEEE Intelligent Vehicles Symposium, 2006.
DOI : 10.1109/IVS.2006.1689643

]. Z. Zha98 and . Zhang, Determining the epipolar geometry and its uncertainty : a review, International Journal of Computer Vision, 1998.

J. [. Zabih and . Woodfill, Non-parametric local transforms for computing visual correspondence, Proceedings of the European Conference on Computer Vision, pp.151-158, 1994.
DOI : 10.1007/BFb0028345

R. [. Zhang, R. A. Weiss, and . Hanson, Qualitative obstacle detection, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94, 1994.
DOI : 10.1109/CVPR.1994.323881