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Emotion recognition from human gait features based on DCT transform
Xue, Penghui1; Li, Baobin1; Wang, Ning2; zhu, Tingshao3
First AuthorXue, Penghui
2019-08
Conference Name5th International Conference on Human Centered Computing, HCC 2019
Correspondent Emailli, baobin ; zhu, tingshao
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11956
Pages511-517
Conference DateAugust 5, 2019 - August 7, 2019
Conference Place不详
PublisherSpringer
Abstract

Emotion recognition is of great value in human-computer interaction, psychology, etc. Gait is an important pattern of emotion recognition. In this paper, 59 volunteer’s gait data with angry or happy emotion, have been collected by the aid of Microsoft Kinect. The gait data are treated as discrete time signals, and we extract a series of frequency features based on the discrete cosine transform. Simultaneously, we have established emotion recognizing models with SVM, the K-nearest neighbors, and decision tree. The best recognition rate can exceed 80%, which indicates that our proposed features are useful for recognizing emotions.

DOI10.1007/978-3-030-37429-7_51
ISBN13:9783030374280
Indexed ByEI
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.psych.ac.cn/handle/311026/31314
Collection社会与工程心理学研究室
Affiliation1.School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing
2.Institute of Psychology Chinese Academy of Sciences, Beijing
3.Beijing Institute of Electronics Technology and Application, Beijing
Recommended Citation
GB/T 7714
Xue, Penghui,Li, Baobin,Wang, Ning,et al. Emotion recognition from human gait features based on DCT transform[C]:Springer,2019:511-517.
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