Robust infrared face recognition based on deformable model
基于形变模型的红外人脸鲁棒识别*

There are three main barriers toward face recognition: the variation of illumination, expression change and occlusion. A method of thermal infrared face image recognition is put forward to tackle illumination change, and an algorithm of integration local deformable model is proposed to overcome the problem of expression change and occlusion. This method cast the thermal infrared test face image as a linear combination of face database and used deformable model representation; Match optimization deformable model for solving combinatorial coefficient, according to the sparse nature of coefficients for classification. To further improve the robustness of the algorithm, use partition-based scheme. Conducting extensive experiments on Equinox databases show that the performance of face recognition based on infrared light is significantly higher than visible light face recognition for the variation of illumination; integrating local deformable model based face recognition can effectively improve the recognition rate, and can overcome the problems of glasses occlusion and expression change.