关键词: 人脸识别, 稀疏表示, 分层框架, 小波特征

Abstract: Few study has been performed on the nonlinear feature selection in the field of sparse representation face recognition. A hierarchical framework for sparse representation face recognition is proposed. First it constructs the face overcompleted dictionary of wavelet low frequency feature and high frequency feature. During the recognition, low frequency feature is used to sparse representation face recognition firstly, and then the category fuzzy coefficient is computed and decided to output the category tag or go on the high frequency sparse representation face recognition. The experimental results show that the face recognition hierarchical framework improves the accuracy of recognition and the framework is robust to face image occlusion.

Key words: face recognition, sparse representation, hierachical framework, wavelet feature