Curve Finder Combining Perceptual Grouping and a Kalman Like Fitting
Abstract
- We present an algorithm that extracts curves from a set of edgels within
a specific class in a decreasing order of their ``length''. The algorithm
inherits the perceptual grouping approaches. But, instead of using only local
cues, a global constraint is imposed to each extracted subset of edgels, that
the underlying curve belongs to a specific class. In order to reduce the complexity
of the solution, we work with a linearly parameterized class of curves, function
of one image coordinate. This allows, first, to use a recursive Kalman based
fitting and, second, to cast the problem as an optimal path search in an directed
graph. Experiments on finding lane-markings on roads demonstrate that real-time
processing is achievable.
Reference
@INPROCEEDINGS{jpt-iccv99,
author = {Guichard, F. and Tarel, J.-P.},
title = {Curve Finder Combining Perceptual Grouping and a Kalman Like Fitting},
booktitle = {IEEE International Conference on Computer Vision (ICCV'99)},
date = {September 20-25},
address = {Kerkyra, Greece},
page = {1003-1008},
year = {1999},
note = {http://perso.lcpc.fr/tarel.jean-philippe/publis/iccv99.html}
}
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