Large-Scale Face Recognition on Smart Devices

Abstract

Most of highly accurate face recognition methods are not suitable for real-time requirement in smart devices which have computational limitations. In this demonstration, we exhibit a face recognition application, in which only essential facial features from images are used for personal identification. In the algorithm used in this application, the face feature size is dramatically compressed into 512 bytes per face in spite of high recognition rate, a false rejection rate of 1.6% at false acceptance rate of 0.1% on identification photos. Consequently, computational cost for face matching is reduced dramatically and the system achieves 1.16 million times matching/second in dual-core 1.5GHz ARM processor. The demonstration on the smart device shows a high recognition performance and the feasibility for diverse applications.