Emotional classification and prediction of body movements based on silhouette
YUAN Hong1,2, WANG Bo1, WANG Li1, XU Mu-xun2
1. National Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing 100094, China;
2. Department of Industrial Design, Xi'an Jiaotong University, Xi'an 710049, China
The features of the human behaviors were collected by camera and extracted with OpenCV in order to predict the emotions of individuals with the help of PAD scales based on previous studies. Ten subjects were requested to express their emotions through body movements, which were induced by Chinese folk music involving positive, middle and negative emotions. The states of subjects' emotions were evaluated by PAD scales while the behaviors of subjects were collected by camera. The features of individual behaviors were extracted with the characteristic of silhouette, including the relative areas of the individual silhouettes and their rate of change. The emotions of behaviors were classified by support vector machine with the evaluation of emotional scales in order to realize the emotional prediction of the behavioral features. The results realized the emotional classification of behaviors, and the prediction accuracy rate came to 76.92% with the categories of positive and negative emotions.
Received: 23 October 2016
Published: 15 December 2017
YUAN Hong, WANG Bo, WANG Li, XU Mu-xun. Emotional classification and prediction of body movements based on silhouette. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(1): 160-165.
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