Face recognition based on committee machine

Face recognition has been of interest to a growing number of researchers, and many algorithms are presented. However, the recognition rate will be significantly reduced in the case of large sample size and greater facial expression changes. In this paper, 2DPCA algorithm is used for features extraction and Boosting by filtering method is used to choose training samples. Then, the expert systems of Committee Machine are constructed and applied in face recognition. Experimental results based on ORL face database and Yale face database show that the recognition rate can be improved effectively.