We present a new application of computer vision: continuous measurement of the geometrical visibility range on inter-urban roads, solely based on a monocular image acquisition system. To tackle this problem, we propose first a road segmentation scheme based on a Parzen-windowing of a color feature space with an original update that allows us to cope with heterogeneously paved-roads, shadows and reflections, observed under various and changing lighting conditions. Second, we address the under-constrained problem of retrieving the depth information along the road based on the flat word assumption. This is performed by a new region-fitting iterative least squares algorithm, derived from half-quadratic theory, able to cope with vanishing-point estimation, and allowing us to estimate the geometrical visibility range.
Backward Segmentation and Region Fitting for Geometrical Visibility Range Estimation
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
Road Region , Pavement Material , Road Boundary , Mobile Robot , Polynomial Curf Pattern Recognition , Artificial Intelligence , Algorithm Analysis and Problem Complexity , Computer Science , Biometrics , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics
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