Research on thermal infrared face alignment method based on regional location

Abstract

Face alignment is a research hotspot in face recognition technology, and face alignment can help improve the recognition accuracy of face recognition. Many face alignment methods have been proposed, such as the visible light face alignment technology based on key facial feature points. However, it is not applicable to thermal infrared face alignment technology. This paper proposes a thermal infrared face alignment technology based on regional positioning, that is, the key feature area of the thermal infrared face image is extracted by the generation confrontation network, and then the key feature area is converted into key feature points, so as to realize the thermal infrared face alignment technology. The data set used in this method is the thermal infrared face data set created by the team of Professor Zhang Tianxu of Huazhong University of Science and Technology. The thermal infrared face image after the alignment operation using this method is input to the FaceNet face recognition network, and the recognition accuracy rate is 95.46%. Compared with the input of misaligned thermal infrared face images, the recognition accuracy is improved by 1.62%. The regional positioning thermal infrared face alignment method proposed in this paper can effectively improve the accuracy of thermal infrared face recognition.