ML Anthology

Part-Based Face Recognition Using near Infrared Images

Ke Pan, Shengcai Liao, Zhijian Zhang, Stan Z. Li, Peiren Zhang
CVPR 2007
doi:10.1109/CVPR.2007.383459 /cvpr/2007/pan2007cvpr-part/

Abstract

Recently, the authors developed NIR based face recognition for highly accurate face recognition under illumination variations. In this paper, we present a part-based method for improving its robustness with respect to pose variations. An NIR face is decomposed into parts. A part classifier is built for each part, using the most discriminative LBP histogram features selected by AdaBoost learning. The outputs of part classifiers are fused to give the final score. Experiments show that the present method outperforms the whole face-based method by 4.53%.

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Cite

Text

Pan et al. "Part-Based Face Recognition Using near Infrared Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383459

Markdown

[Pan et al. "Part-Based Face Recognition Using near Infrared Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/pan2007cvpr-part/) doi:10.1109/CVPR.2007.383459

BibTeX

@inproceedings{pan2007cvpr-part,
  title     = {{Part-Based Face Recognition Using near Infrared Images}},
  author    = {Pan, Ke and Liao, Shengcai and Zhang, Zhijian and Li, Stan Z. and Zhang, Peiren},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383459},
  url       = {https://mlanthology.org/cvpr/2007/pan2007cvpr-part/}
}