【摘要】 基于深度学习的表情动作单元识别是计算机视觉与情感计算领域的热点课题.每个动作单元描述了一种人脸局部表情动作,其组合可定量地表示任意表情.当前动作单元识别主要面临标签稀缺、特征难捕捉和标签不均衡3个挑战因素.基于此,本文将已有的研究分为基于迁移学习、基于区域学习和基于关联学习的方法,对各类代表性方法进行评述和总结.最后,本文对不同方法进行了比较和分析,并在此基础上探讨了未来动作单元识别的研究方向.更多还原

【Abstract】 Expression action unit(AU) recognition based on deep learning is a hot topic in the fields of computer vision and affective computing. Each AU describes a facial local expression action, and the combinations of AUs can quantitatively represent any expression. Current AU recognition mainly faces three challenging factors, scarcity of labels, difficulty of feature capture, and imbalance of labels. On this basis, this paper categorizes the existing researches into transfer learning based, region learning based, and relation learning based methods, and comments and summarizes each category of representative methods. Finally, this paper compares and analyzes different methods, and further discusses the future research directions of AU recognition.更多还原