Detecting Regions from Single Scale Edges
Abstract
We believe that the potential of edges in local feature detection has not been fully exploited and therefore propose a detector that starts from single scale edges and produces reliable and interpretable blob-like regions and groups of regions of arbitrary shape. The detector is based on merging local maxima of the distance transform guided by the gradient strength of the surrounding edges. Repeatability and matching score are evaluated and compared to state-of-the-art detectors on standard benchmarks. Furthermore, we demonstrate the potential application of our method to wide-baseline matching and feature detection in sequences involving human activity.
Cite
Text
Rapantzikos et al. "Detecting Regions from Single Scale Edges." European Conference on Computer Vision, 2010. doi:10.1007/978-3-642-35749-7_23Markdown
[Rapantzikos et al. "Detecting Regions from Single Scale Edges." European Conference on Computer Vision, 2010.](https://mlanthology.org/eccv/2010/rapantzikos2010eccv-detecting/) doi:10.1007/978-3-642-35749-7_23BibTeX
@inproceedings{rapantzikos2010eccv-detecting,
title = {{Detecting Regions from Single Scale Edges}},
author = {Rapantzikos, Konstantinos and Avrithis, Yannis and Kollias, Stefanos D.},
booktitle = {European Conference on Computer Vision},
year = {2010},
pages = {298-311},
doi = {10.1007/978-3-642-35749-7_23},
url = {https://mlanthology.org/eccv/2010/rapantzikos2010eccv-detecting/}
}