Scenario-Based Score Fusion for Face Recognition at a Distance
Abstract
The effect of different acquisition distances on the performance of face verification is studied. In particular, we evaluate two standard approaches using popular features (DCT and PCA) and matchers (GMM and SVM) under variation in the acquisition distance, as well as their score-level combination. The DCT-GMM-based system is found to be more robust to acquisition distance degradation than the PCASVM-based system. We exploit this fact by introducing an adaptive score fusion scheme based on a novel automatic scenario estimation which is shown to improve our system in uncontrolled environments. © 2010 IEEE.
Cite
Text
Tome et al. "Scenario-Based Score Fusion for Face Recognition at a Distance." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010. doi:10.1109/CVPRW.2010.5543231Markdown
[Tome et al. "Scenario-Based Score Fusion for Face Recognition at a Distance." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010.](https://mlanthology.org/cvprw/2010/tome2010cvprw-scenariobased/) doi:10.1109/CVPRW.2010.5543231BibTeX
@inproceedings{tome2010cvprw-scenariobased,
title = {{Scenario-Based Score Fusion for Face Recognition at a Distance}},
author = {Tome, Pedro and Fiérrez, Julian and Alonso-Fernandez, Fernando and Ortega-Garcia, Javier},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2010},
pages = {67-73},
doi = {10.1109/CVPRW.2010.5543231},
url = {https://mlanthology.org/cvprw/2010/tome2010cvprw-scenariobased/}
}