Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition
作者：
Highlights：
• A novel texture extraction method for facial expression recognition is proposed.
• High performance is attained with both posed and spontaneous facial expression.
• Multi-gradient features for magnitude and angle components are derived.
• Multi Classifier System based on the multi-class SVM is adopted.
• Comparison with the state-of-the-art showed the superiority of the method.
摘要
•A novel texture extraction method for facial expression recognition is proposed.•High performance is attained with both posed and spontaneous facial expression.•Multi-gradient features for magnitude and angle components are derived.•Multi Classifier System based on the multi-class SVM is adopted.•Comparison with the state-of-the-art showed the superiority of the method.
论文关键词：Texture feature analysis,Spontaneous facial expression,Multi gradient magnitude and angle images,Elongated quinary pattern,Multi classifier system,Multi-class SVM classifier
论文评审过程：Received 6 December 2016, Revised 9 May 2017, Accepted 1 June 2017, Available online 3 June 2017, Version of Record 12 July 2017.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.06.007
