Automatic Databases for Unsupervised Face Recognition
Abstract
In this paper, an automatic system is presented to establish databases for face recognition from video. We propose a temporal-based face detector, which can improve the detection rate as well as the recognition rate when working together with an image-based face detection method. Several adaptive thresholds and a filter are introduced to improve face recognition performance and to keep the purity, variety and rapidity of the face databases. The system deals with multiple coexisting persons without requirement for any user interaction, and without requirement for any human supervision or assistance.
Cite
Text
Mou et al. "Automatic Databases for Unsupervised Face Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2004. doi:10.1109/CVPR.2004.305Markdown
[Mou et al. "Automatic Databases for Unsupervised Face Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2004.](https://mlanthology.org/cvprw/2004/mou2004cvprw-automatic/) doi:10.1109/CVPR.2004.305BibTeX
@inproceedings{mou2004cvprw-automatic,
title = {{Automatic Databases for Unsupervised Face Recognition}},
author = {Mou, Dengpan and Schweer, Rainer and Rothermel, Albrecht},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2004},
pages = {90},
doi = {10.1109/CVPR.2004.305},
url = {https://mlanthology.org/cvprw/2004/mou2004cvprw-automatic/}
}