Combined Dynamic Tracking and Recognition of Curves with
Application to Road Detection
Abstract
We present an algorithm that extracts the largest shape within a specificclass,
starting from a set of image edgels. The algorithm inherits the Best-First
Segmentation approach [jpt-iccv99]. However, instead
of being applicable only to shapes defined within a given class of curves, we
have extended our approach to tackle more general - and complex - shapes. For
example, we can now process shapes obtained from sets defined over different
kinds of curves and related to one another by estimated parameters. Therefore,
we go from a segmentation problem to a recognition problem. In order to reduce
the complexity of the searching algorithm, we work with a linearly parameterized
class of shapes.
This allows us, first, to use a recursive Least-Squares fitting,
second, to cast the problem as the search of a largest edgel subset in a directed
acyclic graph, and, third, to easily introduce a priori information on the location
of the searched subset. This leads us to propose a unified approach
where recognition and tracking are combined. Experiments on recognizing and
tracking both left and right road boundaries demonstrate that real-time processing
is achievable.
Reference
@inproceedings{jpt-icip2000,
author = {Tarel, J.-P. and Guichard, F.},
title = {Combined Dynamic Tracking and Recognition of Curves with Application to Road Detection},
booktitle = {IEEE International Conference on Image Processing (ICIP'2000)},
date = {September 10-13},
address = {Vancouver, Canada},
year = {2000},
volume = {I},
page = {216-219},
note = {http://perso.lcpc.fr/tarel.jean-philippe/publis/icip00.html}
}
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