Thermal Imaging-Based Human Emotion Detection: GLCM Feature Extraction Approach

Abstract

Recent studies in artificial intelligence and robotics proved the ability of social intelligence in robots. However, it has become increasingly apparent that social and interactive skills are necessary requirements in any application areas and contexts where robots is needed to interact and collaborate with other robots or humans. In order to develop an emotionally intelligent robot, the issues on how to perceive human emotion (affective) states and how to manifest the robot’s emotion should be addressed. In this paper, we presented an efficient method for thermal image feature extraction using the Gray Level Co-occurrence Matrix (GLCM) technique. By analysing the heat pattern on the facial skin, this work attempt to investigate the suitability of the thermal imaging technique for affect detection. The findings of this study indicate thermal imaging as an alternative, contactless and noninvasive method for appraising human emotional states.