关键词: 稀疏编码, 稀疏表示, 人脸识别, 正交匹配追踪, 子空间追踪

Abstract: Against the disadvantage of haven’t update selected atoms in existing face recognition method based on sparse representation, this paper proposes a face recognition based on subspace pursuit. This algorithm introduces back iterative optimization method and polyatomic options in the atomic choice in sparse coding, by removing the candidate atoms with low credibility to make sure that the chosen atoms have the most similar structure with the identifying face image, so the sparse coding coefficient can reconstruct faces well. The experimental results show that this algorithm has lower algorithm complexity and boosts about 5% recognition rate on ORL and Yale B face database compared with Orthogonal Matching Pursuit algorithm（OMP） and the OMP-cholesky algorithm.

Key words: sparse coding, sparse representation, face recognition, Orthogonal Matching Pursuit（OMP）, subspace pursuit