Structured Light Based Depth Edge Detection for Object Shape Recovery
Abstract
This research features a novel approach that efficiently detects depth edges in real world scenes. Depth edges play a very important role in many computer vision problems because they represent object contours. We strategically project structured light and exploit distortion of light pattern in the structured light image along depth discontinuities to reliably detect depth edges. Distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. For practical application of the proposed approach, we have presented methods that guarantee the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show that the proposed method accurately detect depth edges of human hand and body shapes as well as general objects.
Cite
Text
Kim et al. "Structured Light Based Depth Edge Detection for Object Shape Recovery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005. doi:10.1109/CVPR.2005.536Markdown
[Kim et al. "Structured Light Based Depth Edge Detection for Object Shape Recovery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005.](https://mlanthology.org/cvprw/2005/kim2005cvprw-structured/) doi:10.1109/CVPR.2005.536BibTeX
@inproceedings{kim2005cvprw-structured,
title = {{Structured Light Based Depth Edge Detection for Object Shape Recovery}},
author = {Kim, Cheolhwon and Park, Jiyoung and Yi, Juneho and Turk, Matthew},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2005},
pages = {106},
doi = {10.1109/CVPR.2005.536},
url = {https://mlanthology.org/cvprw/2005/kim2005cvprw-structured/}
}