Accelerated robust sparse coding for fast face recognition

Guanglu Liu, Yan Yan, Hanzi Wang

Abstract: In this paper, we propose an accelerated robust sparse coding (ARSC) method which is based on the combination of linear-regression based classification and robust sparse coding for fast face recognition. First, linear-regression based classification (LRC) is used to select the candidate face set, which can effectively reduce the search scope. Then, robust sparse coding (RSC) is applied to perform accurate face identification in the selected face set. Extensive experimental results on various face databases demonstrate that the proposed ARSC can greatly reduce the computational complexity while achieving high recognition performance.