Joint Spatial Geometric and Max-margin Classifier Constraints for Facial Expression Recognition Using Nonnegative Matrix Factorization

Abstract

In this paper, we propose a new approach to facial expression recognition based on the constrained non-negative matrix factorization algorithm. Our proposed method incorporated two tasks in an automatic expression analysis system: facial feature extraction and classification into expressions. To obtain local and geometric structure information in the data as much as possible, we unite max-margin classification into the constrained NMF optimization, resulting in a multiplicative updating algorithm is also proposed for solving optimization problem. Experimental results on JAFFE dataset demonstrate that the effectiveness of the proposed method with improved performances over the conventional dimension reduction methods.