Multiple features fusion for facial expression recognition based on ELM
Lingzhi Yang, Xiaojuan Ban, Yitong Li, Guang Zhong Yang · International Journal of Embedded Systems · 2018
Traditional facial expression recognition includes a feature extractor and a classifier. In this paper, multiple features fusion approaches for facial expression recognition are proposed to improve the recognition accuracy. We consider a feature level fusion method, serial feature fusion, and decision level fusion, linear opinion pool, to combine multiple features. Local binary patterns, local directional number pattern and edge orientation histograms are used to extract features. Then, extreme learning machine is used as the classifier for expression classification. Experiments on JAFFE and CK+ show the method achieves better results.