Human emotion recognition from facial thermal image based on fused statistical feature and multi-class SVM

Affective computing has become a growing field of research activities due to its wide use of application in human computer interface. Emotion recognition is one of the state-of-the-art techniques in determining current psychological state of human being. Human emotions are very overlapping in nature and thus it needs an efficient feature-extractor and classifier assembly. This paper reports a novel non-invasive technique to classify human emotion through thermal images of face. Hu's moment invariants of different patches have been fused with histogram statistical feature and used as robust features in multiclass support vector machine based classification. It is found that emotions from thermal image can be classified by the proposed method with a satisfactory performance.