Rapid Face Recognition Using Hashing
Q Shi, Hanxi Li and Chunhua Shen
In: Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), San Francisco, USA(2010).
We propose a face recognition approach based on hashing. The approach yields comparable recognition rates with the random l approach , which is considered the state-of-the-art. But our method is much faster: it is up to 150 times faster than  on the YaleB dataset. We show that with hashing, the sparse representation can be recovered with a high probability because hashing preserves the restrictive isometry property. Moreover, we present a theoretical analysis on the recognition rate of the proposed hashing approach. Experiments show a very competitive recognition rate and signiﬁcant speedup compared with the state-of-the-art.