Segmentation and Recovery of SHGCs from a Real Intensity Image
Abstract
We address the problem of scene segmentation and shape recovery from a single real intensity image. Solving this problem is central to obtaining 3-D scene descriptions in realistic applications where perfect data cannot be obtained and only one image is available. The method we propose addresses a large class of generic shapes, namely straight homogeneous generalized cylinders (SHGCs). It consists of the derivation and use of their geometric projective properties in a multi-level grouping approach. We describe an implemented and working system that detects and recovers full SHGC descriptions in the presence of image imperfections such as broken contours, surface markings, shadows and occlusion. We demonstrate our method on complex real images.
Cite
Text
Zerroug and Nevatia. "Segmentation and Recovery of SHGCs from a Real Intensity Image." European Conference on Computer Vision, 1994. doi:10.1007/3-540-57956-7_36Markdown
[Zerroug and Nevatia. "Segmentation and Recovery of SHGCs from a Real Intensity Image." European Conference on Computer Vision, 1994.](https://mlanthology.org/eccv/1994/zerroug1994eccv-segmentation/) doi:10.1007/3-540-57956-7_36BibTeX
@inproceedings{zerroug1994eccv-segmentation,
title = {{Segmentation and Recovery of SHGCs from a Real Intensity Image}},
author = {Zerroug, Mourad and Nevatia, Ramakant},
booktitle = {European Conference on Computer Vision},
year = {1994},
pages = {319-330},
doi = {10.1007/3-540-57956-7_36},
url = {https://mlanthology.org/eccv/1994/zerroug1994eccv-segmentation/}
}