Better Shading for Better Shape Recovery
Abstract
The basic idea of shape from shading is to infer the shape of a surface from its shading information in a single image. Since this problem is ill-posed, a number of simplifying assumptions have been often used. However they rarely hold in practice. This paper presents a simple shading-correction algorithm that transforms the image to a new image that better satisfies the assumptions typically needed by existing algorithms, thus improving the accuracy of shape recovery. The algorithm takes advantage of some local shading measures that have been driven under these assumptions. The method is successfully evaluated on real data of human teeth with ground-truth 3D shapes.
Cite
Text
El-Melegy et al. "Better Shading for Better Shape Recovery." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.295Markdown
[El-Melegy et al. "Better Shading for Better Shape Recovery." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/elmelegy2014cvpr-better/) doi:10.1109/CVPR.2014.295BibTeX
@inproceedings{elmelegy2014cvpr-better,
title = {{Better Shading for Better Shape Recovery}},
author = {El-Melegy, Moumen T. and Abdelrahim, Aly S. and Farag, Aly A.},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2014},
doi = {10.1109/CVPR.2014.295},
url = {https://mlanthology.org/cvpr/2014/elmelegy2014cvpr-better/}
}