A fuzzy descriptor for analyzing the differences of facial expression
Xiaodong Duan, Zedong Li, Yu Shi, Jinmiao Song, Tao Sun, Xiaodong Zhang · 2018
This paper proposes an improved fuzzy semantic model (IFSM) to analyze the differences of facial expressions. Comparison with traditional methods. Our method has two advantages: (i) The proposed method breaks the image limit such as scale, illumination; (ii) According to fuzzy rules, the method can interpret expression features using semantic concepts. Then, the FEI and CK+ datasets are applied in analyzing the differences among various expressions. At last, in order to compare the performance, the state-of-the-art methods have been executed. The results illustrate our method has a better accuracy, but also can interpret expression features well.