Discriminative Ability Based Facial Expression Recognition Using Kernel Relief Algorithm

摘要

Most existing local feature based facial expression recognition system have concentrate on the salient region on the face, while the effectiveness of the selected region and the computational complexity of the system still need improved. To overcome the limits of the previous work, we propose a novel algorithm kernel ReliefF to select the discriminative patches on the face. The novel approach not only considers the whole feature but also enhances the locality of the variation of the expressive face. Furthermore, it takes less computational complexity. Experimental results on CK+ and RML demonstrate that the method significantly outperforms the state-of-the-art.