General Road Detection From a Single Image

Hui Kong 1 Jean-Yves Audibert 1, 2, 3 Jean Ponce 1
1 WILLOW - Models of visual object recognition and scene understanding
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
2 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
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 upon the detected vanishing point. The main technical contributions of the proposed approach are a novel adaptive soft voting scheme based upon a local voting region using high-confidence voters, whose texture orientations are computed using Gabor filters, 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 effective at detecting road regions in challenging conditions.
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Contributeur : Jean-Yves Audibert <>
Soumis le : mercredi 21 décembre 2011 - 17:47:37
Dernière modification le : jeudi 7 février 2019 - 15:49:18



Hui Kong, Jean-Yves Audibert, Jean Ponce. General Road Detection From a Single Image. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2010, 19 (8), pp.2211-2220. ⟨10.1109/TIP.2010.2045715⟩. ⟨hal-00654397⟩



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