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Emotion detection using Kinect 3D facial points
Zhang Z.1; Cui L.2; Liu XQ(刘晓倩)2; Zhu T.2; Xiaoqian Liu; Tingshao Zhu
2016
Conference Name2016 IEEE/WIC/ACM International Conference on Web Intelligence
Correspondent Emailliuxiaoqian@psych.ac.cn ; tszhu@psych.ac.cn
Conference DateOct.13-16 2016
Conference PlaceUSA
Abstract

Abstract—With the development of pattern recognition and artificial intelligence, emotion recognition based on facial expression has attracted a great deal of research interest. Facial emotion recognition are mainly based on facial images. The commonly used datasets are created artificially, with obvious facial expression on each facial images. Actually, emotion is a complicated and dynamic process. If a person is happy, probably he /she may not keep obvious happy facial expression all the time. Practically, it is important to recognize emotion correctly even if the facial expression is not clear. In this paper, we propose a new method of emotion recognition, i.e., to identify three kinds of emotion: sad, happy and neutral. We acquire 1347 3D facial points by Kinect V2:0. Key facial points are selected and feature extraction is conducted. Principal Component Analysis (PCA) is employed for feature dimensionality reduction. Several classical classifiers are used to construct emotion recognition models. The best performance of classification on all, male and female data are 70%, 77% and 80% respectively. 

KeywordEmotion recognition Facial expression Kinect
Indexed By其他
Language英语
Document Type会议论文
Identifierhttp://ir.psych.ac.cn/handle/311026/20898
Collection社会与工程心理学研究室
Corresponding AuthorXiaoqian Liu; Tingshao Zhu
Affiliation1.School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China
2.中国科学院心理研究所
Recommended Citation
GB/T 7714
Zhang Z.,Cui L.,Liu XQ,et al. Emotion detection using Kinect 3D facial points[C],2016.
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