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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
Conference Name2016 IEEE/WIC/ACM International Conference on Web Intelligence
Correspondent ;
Conference DateOct.13-16 2016
Conference PlaceUSA

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
Document Type会议论文
Corresponding AuthorXiaoqian Liu; Tingshao Zhu
Affiliation1.School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China
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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