Robust Face Recognition System Using a Reliability Feedback

摘要

In the real world there are a variety of lighting conditions, and there exist many directional lights as well as ambient lights. These directional lights cause partial dark and bright regions on faces. Even if auto exposure mode of cameras is used, those uneven pixel intensities are left, and in some cases saturated pixels and black pixels appear. In this paper we propose robust face recognition system using a reliability feedback. The system evaluates the reliability of the input face image using prior distributions of each recognition feature, and if the reliability of the image is not enough for face recognition, it capture multiple images by changing exposure parameters of cameras based on the analysis of saturated pixels and black pixels. As a result the system can cumulates similarity scores of enough amounts of reliable recognition features from multiple face images. By evaluating the system in an office environment, we can achieve three times better EER than the system only with auto exposure control.