Thermal Facial Landmark Detection by Deep Multi-Task Learning

We present a neural network to jointly consider facial landmark detection and emotion recognition for thermal face images. The first part of this network is based on the U-Net structure, targeting at extracting good features for advanced analysis. Using U - Net as the basic structure enables modeling context information based on a limited number of training data. The second part of this network contains two branches that are designed for landmark detection and emotion recognition, respectively. We propose a two-stage training mechanism to learn this network, and demonstrate the effectiveness of the proposed approach. This work is believed to be one of the few studies on thermal face image analysis.