Estimation :

• Traitement d'image
• SLAM
• Vision par ordinateur, perception multi-capteur

Revues :

Lu W., Rodriguez Florez S., Seignez E. and Reynaud R., Lane marking-based vehicle localization using low-cost GPS, Journal of Unmanned Systems, Special Issue: Vision for Robots, 3(4):239-251, 2015.

Rodriguez Florez S., Fremont V., Bonnifait P. and Cherfaoui V., Multi-modal object detection and localization for high integrity driving assistance, Machine Vision and Applications, 25(3):583-598, 2014.

Rodriguez Florez S., Fremont V., Bonnifait P. and Cherfaoui V., An embedded multi-modal system for object localization and tracking, IEEE Intelligent Transportation Systems Magazine, 4(4):42-53, 2012.

Fremont V., Rodriguez Florez S. and Bonnifait P. Circular targets for 3D alignment of video and lidar sensors, Advanced Robotics, 26(18):2087-2113, 2012. DOI: 10.1080/01691864.2012.703235

Conférences internationales avec actes :

Sattarov E., Gepperth A., Rodriguez Florez S. et Reynaud R., "Calibration-free correspondence finding between vision and LIDAR sensors", IEEE International Symposium on Intelligent Vehicles (IV), 2015.

Gepperth A., Sattarov E., Heisele B. and Rodriguez Florez S., A. Robust visual pedestrian detection by tight coupling to tracking, 17th International IEEE Conference on Intelligent Transportation Systems, 2014.

Hu X., Rodriguez Florez S. and Gepperth A., A Multi-Modal System for Road Detection and Segmentation, IEEE Intelligent Vehicles Symposium 2014, in Dearborn, Michigan, United States, 2014, pp. 1365-1370.

Lu W., Seignez E., Rodriguez Florez S. and Reynaud R., Lane Marking Based Vehicle Localization using Particle Filter and Multi-Kernel Estimation, IEEE International Conference On Control Automation Robotics and Vision (ICARCV), in Singapore, pp 601-606 (ISBN 978-1-4799-5199-4), Best paper award.

Lu W., Rodriguez Florez S., Seignez E. and Reynaud R., Probabilistic Error Model for a Lane Marking Based Vehicle Localization Coupled to Open Source Maps, IEEE International Conference on Intelligent Transportation Systems (ITSC), in Qingdao, China, 2014, pp 360-365 (ISBN 978-1-4799-6077-4).

Lu W., Rodriguez Florez S., Seignez E. and Reynaud R., Monocular Multi-Kernel Based Lane Marking Detection, IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), in Hong Kong, China, 2014, pp 123-128 (ISBN 978-1-4799-3668-7).

Sattarov E., Rodriguez Florez S., Gepperth A. et Reynaud R l., "Context-based vector fields for multi-object tracking in application to road traffic", 17th International IEEE Conference on Intelligent Transportation Systems, 2014, pp. 1179-1185. Doi: 10.1109/ITSC.2014.6957847

Wang B., Rodriguez Florez S. and Fremont V., Multiple Obstacle Detection and Tracking using Stereo Vision: Application and Analysis, International Conference on Control, Automation, Robotics and Vision [IEEE], 2014, pp. 1074-1079.

Wang B., Fremont V. and Rodriguez Florez S., Color-Based Road Detection and Its Evaluation on the KITTI Road Benchmark, 2014 IEEE Intelligent Vehicles Symposium, in United States, 2014, 6p.

Lu W., Rodriguez Florez S., Seignez E. and Reynaud R., An Improved Approach for Vision-Based Lane Marking Detection and Tracking, International Conference on Electrical, Control and Automation Engineering, in Hong Kong, China, 2013, pp 382-386 (ISBN 978-1-60595-148-5).

Liste des Thèses soutenues depuis le premier janvier 2012 :

Mr. Wenjie LU. Thèse en co-encadrement de R. Reynaud, S. Rodriguez, E. Seignez. Titre : Contributions to Lane Marking Based Localization for Intelligent Vehicles., de 10/2012-à 02/2015, financement CSC, 1 revue, 4 conférences.

Mr. Bihao WANG. Thèse en co-direction de S. Rodriguez à 50 % et V. Fremont à l'Université de Technologie de Compiègne. Titre : Moving object detection and tracking. De Sep. 2012 à Jul. 2015. Financement : China Scholarship Council Grant (CSC). Production scientifique : 2 conférences.

Thèses en cours :

Mr Egor SATTAROV. Sujet : Study and quantification of the contribution of multimodal perception systems assisted by context information in the detection and tracking of dynamic objects. Co-encadrement à 33 % R. Reynaud, S. Rodriguez et A. Gepperth de l'ENSTA. Débutée en Dec. 2013. Financement : Digiteo Grant. Production scientifique : 3 conf.