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Conference Papers Year : 2009

Vanishing point detection for road detection

Abstract

Given a single image of an arbitrary road, that may not be well-paved, or have clearly delineated edges, or some a priori known color or texture distribution, is it possible for a computer to find this road? This paper addresses this question by decomposing the road detection process into two steps: the estimation of the vanishing point associated with the main (straight) part of the road, followed by the segmentation of the corresponding road area based on the detected vanishing point. The main technical contributions of the proposed approach are a novel adaptive soft voting scheme based on variable-sized voting region using confidence-weighted Gabor filters, which compute the dominant texture orientation at each pixel, and a new vanishing-point-constrained edge detection technique for detecting road boundaries. The proposed method has been implemented, and experiments with 1003 general road images demonstrate that it is both computationally efficient and effective at detecting road regions in challenging conditions.
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Dates and versions

hal-00834892 , version 1 (17-06-2013)

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Cite

Hui Kong, Jean-Yves Audibert, Jean Ponce. Vanishing point detection for road detection. CVPR 2009 - IEEE Conference on Computer Vision and Pattern Recognition, Jun 2009, United States. pp.96-103, ⟨10.1109/CVPR.2009.5206787⟩. ⟨hal-00834892⟩
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