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Presents a road obstacle detection method able to cope with uphill and downhill gradients and dynamic pitching of the vehicle. Our approach is based on the construction and investigation of the "v-disparity" image which provides a good representation of the geometric content of the road scene. The advantage of this image is that it provides semi-global matching and is able to perform robust obstacle detection even in the case of partial occlusion or errors committed during the matching process. Furthermore, this detection is performed without any explicit extraction of coherent structures. This paper explains the construction of the "v-disparity" image, its main properties, and the obstacle detection method. The longitudinal profile of the road is estimated and the objects located above the road surface are then extracted as potential obstacles; subsequently, the accurate detection of road obstacles, in particular the position of tyre-road contact points is computed in a precise manner. The whole process is performed at frame rate with a current-day PC. Our experimental findings and comparisons with the results obtained using a flat geometry hypothesis show the benefits of our approach.
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Raphaël Labayrade
École Nationale des Travaux Publics de l'État
D. Aubert
Saint-Gobain (France)
Jean‐Philippe Tarel
Université Gustave Eiffel
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Labayrade et al. (Wed,) studied this question.
synapsesocial.com/papers/6a222ad8505988242b494c27 — DOI: https://doi.org/10.1109/ivs.2002.1188024