Road approximation in Euclidean and υ-disparity space: a comparative study

Authors:
Angel D. Sappa;Rosa Herrero;Fadi Dornaika;David Gerónimo;Antonio López
Affiliations:
Computer Vision Center, UAB, Bellaterra, Barcelona, Spain;Computer Vision Center, UAB, Bellaterra, Barcelona, Spain;Institut Géographique National, Saint Mandé, France;Computer Vision Center, UAB, Bellaterra, Barcelona, Spain;Computer Vision Center, UAB, Bellaterra, Barcelona, Spain
Venue:
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Year:
2007

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Abstract

This paper presents a comparative study between two road approximation techniques--planar surfaces--from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces (e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene's prior knowledge.