3D Face Recognition in the Conception of Sparse Representation

In this paper, a novel 3D face recognition method is proposed from the sparse representation point of view. Under the framework of sparse representation, the recognition problem is transformed to solve the problem of minimization L-0-norm. Three types of facial geometrical features are extracted to describe 3D faces. According to the extracted features, 3D face recognition is conducted by applying to the ranking strategy of Fisher linear discriminant analysis. The experiments employed BJUT-3D datasets demonstrate the effectiveness of the proposed method.