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