Multi-Objective Differential Evolution for feature selection in Facial Expression Recognition systems
作者：
Highlights：
• Feature selection using Multi-Objective Differential Evolution (DEMO) is proposed.
• This efficient selection is integrated in advanced Facial Emotion Recognition system.
• ‘Emotion-specific’ and ‘more discriminative features over all emotions’ selection strategies.
• Emotion recognition accuracy of proposed algorithm comparable to state-of-the-art.
• Feature selection by using DEMO enormously reduces a feature vector length.
摘要
•Feature selection using Multi-Objective Differential Evolution (DEMO) is proposed.•This efficient selection is integrated in advanced Facial Emotion Recognition system.•‘Emotion-specific’ and ‘more discriminative features over all emotions’ selection strategies.•Emotion recognition accuracy of proposed algorithm comparable to state-of-the-art.•Feature selection by using DEMO enormously reduces a feature vector length.
论文关键词：Facial Expression Recognition,Feature selection,Differential evolution,Feature vector differences,Multi-objective optimization
论文评审过程：Received 31 January 2017, Revised 23 June 2017, Accepted 23 July 2017, Available online 24 July 2017, Version of Record 28 July 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.07.037
