Spotting Rapid Facial Movements from Videos Using Appearance-Based Feature Difference Analysis
Spotting micro-expressions is a primary step for continuous emotion recognition from videos. Spotting in this context refers to automatically finding the temporal locations of the face-related events from a video sequence. Rapid facial movements mainly include micro-expressions and eye blinks. However, the role of eye blinks in expressing emotions is still controversial, and often they are considered as micro-expressions as well. In this paper a simple method for automatically spotting rapid facial movements from videos is proposed. The method relies on analyzing differences in appearance-based features of sequential frames. In addition to finding the temporal locations, the system is able to provide spatial information about the movements in the face. Micro-expression spotting experiments are carried out on three datasets consisting only of spontaneous micro-expressions. Baseline micro-expression spotting results are provided for these three datasets including the publicly available CASME database. Also an example of spatial localization of the spotted rapid movements is presented.