Proposition of Generic Validation Criteria using stereo-vision for On-Road Obstacle Detection

Abstract : Real-time obstacle detection is an essential function for the future of Advanced Driver Assistance Systems (ADAS), but its applications to the driving safety require a very high reliability: the detection rate must be high, while the false detection rate must remain extremely low. Such features seem antinomic for obstacle detection systems, especially when using a single sensor. Multi-sensor fusion is often considered as a mean to reduce this limitation. In this paper, we propose to use stereo-vision as a post-process to improve the reliability of any obstacle detection system, by reducing the number of false positives. Our algorithm, which is both generic and real-time confirms detections by locally using the stereoscopic data. We evaluated and validated our approach with an initial detection based on a vision system and a laser scanner. The evaluation dataset is real on-road data and contains more than 20000 images.
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International Journal of Robotics and Automation, ACTA Press, 2014, 29 (1), pp 65-87. 〈10.2316/Journal.206.2014.1.206-3765〉
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Soumis le : mercredi 8 octobre 2014 - 12:11:42
Dernière modification le : jeudi 11 octobre 2018 - 08:48:02

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Mathias Perrollaz, Raphaël Labayrade, Dominique Gruyer, Alain Lambert, Didier Aubert. Proposition of Generic Validation Criteria using stereo-vision for On-Road Obstacle Detection. International Journal of Robotics and Automation, ACTA Press, 2014, 29 (1), pp 65-87. 〈10.2316/Journal.206.2014.1.206-3765〉. 〈hal-01072526〉

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