Deep Learning Approach: Emotion Recognition from Human Body Movements


R. Santhoshkumar,M. Kalaiselvi Geetha,



Emotion Recognition,Non-verbal communication,Body Movement,Human Computer Interaction (HCI),Deep Convolutional Neural Networks (DCNN),BAIVfeature,


Analysis of human body movements for emotion prediction is necessary for social communication. Body movements, gestures, eye movements and facial expression are some non-verbal communication method used in many applications. Among them emotion prediction from body movements is commonly used because it convey the emotional states of person from different camera view. In this paper, human emotional states predict from full body movements using feed forward deep convolution neural network architecture and Block Average Intensity Value BAIV feature. Both model can be evaluated by emotion action dataset (University of YORK) with 15 types of emotions. The experimental result showed the better recognition accuracy of the feed forward deep convolution neural network architecture.


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