Face Recognition Via Weighted Two Phase Test Sample Sparse Representation

摘要

Sparse representation (SR) for signals over an overcomplete dictionary fascinates a lot of researchers in the past decade. The two-phase test sample sparse representation method (TPTSSR) achieved an excellent performance in face recognition. However, TPTSSR exploits the global information and tends to lose local information. In this paper, the weighted two phase test sample sparse representation method (WTPTSSR) is proposed. WTPTSSR utilizes both data locality and linearity and it can be regarded as extensions of TPTSSR. Experiments on the face databases demonstrate that WTPTSSR is more effective than TPTSSR.