Illumination Normalization Using Self-Lighting Ratios for 3D2D Face Recognition
Abstract
3D2D face recognition is beginning to gain attention from the research community. It takes advantage of 3D facial geometry to normalize the head pose and registers it into a canonical 2D space. In this paper, we present a novel illumination normalization approach for 3D2D face recognition which does not require any training or prior knowledge on the type, number, and direction of the lighting sources. Estimated using an image-specific filtering technique in the frequency domain, a self-lighting ratio is employed to suppress illumination differences. Experimental results on the UHDB11 and FRGC databases indicate that the proposed approach improves the performance significantly for face images with large illumination variations.
Cite
Text
Zhao et al. "Illumination Normalization Using Self-Lighting Ratios for 3D2D Face Recognition." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33868-7_22Markdown
[Zhao et al. "Illumination Normalization Using Self-Lighting Ratios for 3D2D Face Recognition." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/zhao2012eccv-illumination/) doi:10.1007/978-3-642-33868-7_22BibTeX
@inproceedings{zhao2012eccv-illumination,
title = {{Illumination Normalization Using Self-Lighting Ratios for 3D2D Face Recognition}},
author = {Zhao, Xi and Shah, Shishir K. and Kakadiaris, Ioannis A.},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {220-229},
doi = {10.1007/978-3-642-33868-7_22},
url = {https://mlanthology.org/eccv/2012/zhao2012eccv-illumination/}
}