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 on 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, a function of one image coordinate. This first allows one to use recursive Kalman based fitting and, second, to cast the problem as an optimal path search in a directed graph. Experiments on finding lane-markings on roads demonstrate that real-time processing is achievable.
Cite
Text
Guichard and Tarel. "Curve Finder Combining Perceptual Grouping and a Kalman like Fitting." IEEE/CVF International Conference on Computer Vision, 1999. doi:10.1109/ICCV.1999.790378Markdown
[Guichard and Tarel. "Curve Finder Combining Perceptual Grouping and a Kalman like Fitting." IEEE/CVF International Conference on Computer Vision, 1999.](https://mlanthology.org/iccv/1999/guichard1999iccv-curve/) doi:10.1109/ICCV.1999.790378BibTeX
@inproceedings{guichard1999iccv-curve,
title = {{Curve Finder Combining Perceptual Grouping and a Kalman like Fitting}},
author = {Guichard, Frédéric and Tarel, Jean-Philippe},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1999},
pages = {1003-1008},
doi = {10.1109/ICCV.1999.790378},
url = {https://mlanthology.org/iccv/1999/guichard1999iccv-curve/}
}