Thermal face recognition using convolutional neural network
Zhan Wu, Min Peng, Tong Chen · 2016
With the rapidly development of the face recognition (FR), thermal face recognition has received increasing attention. However, the traditional methods for thermal face recognition mainly concentrate on the hand-crafted feature design, which requires more efforts from human to select and extract features and usually has relatively lower recognition rate. In this paper, we present a convolutional neural network (CNN) architecture for thermal face recognition. CNN is a new type of neural network method which can automatically learn effective features from the raw data. Experiment results on RGB-D-T face database show that our proposed CNN architecture achieves higher recognition rate compared with the traditional recognition such as LBP, HOG and moments invariant.