Fuzzy qualitative approach for micro-expression recognition

Abstract

Micro-expression recognition has received increasing attention in the field of computer vision nowadays. Many state-of-the-art approaches have been reported but it can be seen that most of the results are capped at a certain level of accuracy. This is due to the ambiguity that abounded during the extraction of extremely short period of facial movements. These ambiguities deteriorate the performance of the overall recognition rate if using crisp classifier. This paper proposed to study the micro-expression as a non-mutual exclusive classification problem and examine the effectiveness of multi-label classification in micro-expression recognition by using the Fuzzy Qualitative Rank Classifier (FQRC). In addition, the extension of FQRC with feature selection and part-based model is proposed which shows promising results after tested on CASME II dataset.