Direct Estimation of Non-Rigid Registrations with Image-Based Self-Occlusion Reasoning
Abstract
The registration problem for images of a deforming surface has been well studied. External occlusions are usually well-handled. In 2D image-based registration, self- occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based non-rigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, i.e. direct, data term for registration. Self-occlusions are detected as shrinking areas in the 2D warp. Experimental results on several challenging datasets show that our approach successfully registers images with self-occlusions while effectively detecting the occluded regions.
Cite
Text
Gay-Bellile et al. "Direct Estimation of Non-Rigid Registrations with Image-Based Self-Occlusion Reasoning." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4408989Markdown
[Gay-Bellile et al. "Direct Estimation of Non-Rigid Registrations with Image-Based Self-Occlusion Reasoning." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/gaybellile2007iccv-direct/) doi:10.1109/ICCV.2007.4408989BibTeX
@inproceedings{gaybellile2007iccv-direct,
title = {{Direct Estimation of Non-Rigid Registrations with Image-Based Self-Occlusion Reasoning}},
author = {Gay-Bellile, Vincent and Bartoli, Adrien and Sayd, Patrick},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2007},
pages = {1-6},
doi = {10.1109/ICCV.2007.4408989},
url = {https://mlanthology.org/iccv/2007/gaybellile2007iccv-direct/}
}