Emotion Recognition from 3D Images with Non-Frontal View Using Geometric Approach

Over the last decade emotion recognition has gained prominence for its applications in the field of Human Robot Interaction (HRI), intelligent vehicle, patient health monitoring, etc. The challenges in emotion recognition from non-frontal images, motivates researchers to explore further. In this paper, we have proposed a method based on geometric features, considering 4 yaw angles (0 degrees, + 15 degrees, + 30 degrees, + 45 degrees) from BU-3DFE database. The novelty in our proposed work lies in identifying the most appropriate set of feature points and formation of feature vector using two different approaches. Neural network is used for classification. Among the 6 basic emotions four emotions i.e., anger, happy, sad and surprise are considered. The results are encouraging. The proposed method may be implemented for combination of pitch and yaw angles in future.