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Journal Article

Citation

Perrollaz M, Labayrade R, Gruyer D, Lambert A, Aubert D. Int. J. Robot. Automat. (Calgary) 2014; 29(1): 65-87.

Copyright

(Copyright © 2014, Acta Press)

DOI

10.2316/Journal.206.2014.1.206-3765

PMID

unavailable

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.


Language: en

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