Extended Marginal Fisher Analysis Based on Difference Criterion
Jijian Liu · Journal of Information and Computational Science · 2013
The reasonable construction of neighbor graph plays an important impact to improve the efficiency of face recognition in Marginal Fisher Analysis (MFA) algorithm. In this paper, a new method of constructing neighbor graph is proposed to improve the recognition accuracy of MFA. Specifically, we try to map the raw data of the training samples to a new feature space z, then we select the nearest neighbor points directly based on the new distances, thereby constructing the graph. In addition, we also introduce a new criterion function, which can overcome some shortcomings of MFA. The contrastive experiments on several benchmark face databases show the effectiveness of proposed method.