关键词: 微表情识别, 个性化学习, 中级特征

Abstract: Micro-expressions are fleeting facial expressions that expose a genuine emotions that a person tries to conceal. An existing multi-task middle-level feature learning is improved, and a multi-task middle-level feature individualization learning method for micro-expression recognition is proposed. The same kind of micro-expressions of the same person are removed for calculating its interclass nearest neighbors. the different kind of micro-expressions of the same person are retained and the [k] value is reduced for calculating its interclass nearest neighbors. A middle-level feature with more discriminative information is generated by individualization learning method. Experimental results on spontaneous micro-expression database CASME2 show that the proposed method has better recognition performance.

Key words: micro-expression recognition, individualization learning, middle-level feature