Research on Maximum Likelihood Sparse Coding in Face Recognition
Shan Guiju · Video Engineering · 2013
Sparse coding( SRC) is an effective method for face recognition. The detected image is represented as a sparse linear combination of a set of training samples,the accuracy represented by L2 or L1 norm residue to measure. This model assumes that the encoding residual items Gaussian or Laplace distribution. In fact it can not be very accurate description of coding error rate. In this paper,a new sparse coding method is proposed to establish a model of constrained regression problems. SRC for finding the maximum likelihood estimation parameters of this model has a strong robustness to abnormal situations,namely MSC. The experimental results on Yale and ORL database show the effectiveness and robustness of the method for the human face blurred,illumination and expression changes.