A main directional maximal difference analysis for spotting facial movements from long-term videos

作者：Wang, Su-Jing^*; Wu, Shuhang; Qian, Xingsheng; Li, Jingxiu; Fu, Xiaolan

来源：Neurocomputing, 2017, 230: 382-389.

DOI：10.1016/j.neucom.2016.12.034

• Micro-expression recognition
• Macro-expression
• Micro-expression spotting
• Optical flow

There is an increasing interests in micro-expression researches. Spotting micro-expressions in long-term videos is very important, not only for providing clues for lie detection, but also for reducing the labor required to collect micro-expression data. However, little progress has been made in spotting micro-expressions. In this paper, we propose a Main Directional Maximal Difference (MDMD) Analysis for micro-expression spotting. MDMD uses the magnitude maximal difference in the main direction of optical flow features to spot facial movements, including micro-expressions. Using block structured facial regions, MDMD obtains more accurate features of movement of expressions for automatically spotting micro-expressions and macro-expressions from videos. This method involves both the temporal and spatial locations of face movements. Evaluations using the CAS(ME)(2) database containing micro-expressions and macro-expressions show that MDMD is more robust than some state-of-the-art algorithms.

• 出版日期2017-3-22
• 单位中国科学院; 中国科学院大学; 脑与认知科学国家重点实验室; 哈尔滨医科大学; 东北大学