A Polarimetric Thermal Database for Face Recognition Research
Abstract
We present a polarimetric thermal face database, the first of its kind, for face recognition research. This database was acquired using a polarimetric longwave infrared imager, specifically a division-of-time spinning achromatic retarder system. A corresponding set of visible spectrum imagery was also collected, to facilitate crossspectrum (also referred to as heterogeneous) face recognition research. The database consists of imagery acquired at three distances under two experimental conditions: neutral/baseline condition, and expressions condition. Annotations (spatial coordinates of key fiducial points) are provided for all images. Cross-spectrum face recognition performance on the database is benchmarked using three techniques: partial least squares, deep perceptual mapping, and coupled neural networks.
Cite
Text
Hu et al. "A Polarimetric Thermal Database for Face Recognition Research." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016. doi:10.1109/CVPRW.2016.30Markdown
[Hu et al. "A Polarimetric Thermal Database for Face Recognition Research." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016.](https://mlanthology.org/cvprw/2016/hu2016cvprw-polarimetric/) doi:10.1109/CVPRW.2016.30BibTeX
@inproceedings{hu2016cvprw-polarimetric,
title = {{A Polarimetric Thermal Database for Face Recognition Research}},
author = {Hu, Shuowen and Short, Nathaniel J. and Riggan, Benjamin S. and Gordon, Christopher and Gurton, Kristan P. and Thielke, Matthew and Gurram, Prudhvi and Chan, Alex L.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2016},
pages = {187-194},
doi = {10.1109/CVPRW.2016.30},
url = {https://mlanthology.org/cvprw/2016/hu2016cvprw-polarimetric/}
}