Backward Segmentation and Region Fitting for Geometrical
Visibility Range Estimation
Abstract
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.
Reference
@inproceedings{jpt-accv07,
author = {Bigorgne, E. and Tarel, J.-P.},
title = {Backward Segmentation and Region Fitting for Geometrical Visibility Range Estimation},
booktitle = {Proceedings of Asian Conference on Computer Vision (ACCV'07)},
address = {Tokyo, Japan},
volume = {II},
pages = {817-826},
date = {November 18-22},
year = {2007},
note = {http://perso.lcpc.fr/tarel.jean-philippe/publis/accv07.html}
}
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