A Polarimetric Thermal Database for Face Recognition Research

Shuowen Hu, Nathaniel J. Short, Benjamin S. Riggan, Christopher Gordon, Kristan P. Gurton, Matthew Thielke, Prudhvi Gurram, Alex L. Chan

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.