Optimal Point Correspondence Through the Use of Rank Constraints
Abstract
We propose a solution to the n-frame correspondence problem under the factorization framework. During the matching process, our algorithm takes explicitly into account the geometrical constraints associated to the reconstruction process. To this end, a rank constraint is imposed on the measurement matrix. Since our method relies solely on geometric constraints, it is not dependent on corners as image features and can consequently match generic points (e.g. contours). Outlier rejection is integrated as a part of the actual matching process. In general the problem is formulated as combinatorial, but we develop a method, which can provide a solution with a low computational complexity. Because of this, our algorithm is able to handle high-dimensional matching problems that are common in real-life applications.
Cite
Text
Oliveira et al. "Optimal Point Correspondence Through the Use of Rank Constraints." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.264Markdown
[Oliveira et al. "Optimal Point Correspondence Through the Use of Rank Constraints." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/oliveira2005cvpr-optimal/) doi:10.1109/CVPR.2005.264BibTeX
@inproceedings{oliveira2005cvpr-optimal,
title = {{Optimal Point Correspondence Through the Use of Rank Constraints}},
author = {Oliveira, Ricardo and Costeira, João Paulo and Xavier, João Manuel Freitas},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2005},
pages = {1016-1021},
doi = {10.1109/CVPR.2005.264},
url = {https://mlanthology.org/cvpr/2005/oliveira2005cvpr-optimal/}
}