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Identifying Emotions from Non-Contact Gaits Information Based on Microsoft Kinects
Li, Baobin1; Zhu, Changye1; Li, Shun2; Zhu, Tingshao3
Corresponding AuthorLi, Baobin(libb@ucas.ac.cn)
2018-10-01
Source PublicationIEEE TRANSACTIONS ON AFFECTIVE COMPUTING
ISSN1949-3045
Volume9Issue:4Pages:585-591
AbstractAutomatic emotion recognition from gaits information is discussed in this paper, which has been investigated widely in the fields of human-machine interaction, psychology, psychiatry, behavioral science, etc. The gaits information is non-contact, collected from Microsoft kinects, and contains 3-dimensional coordinates of 25 joints per person. These joints coordinates vary with the time. So, by the discrete Fourier transform and statistic methods, some time-frequency features related to neutral, happy and angry emotion are extracted and used to establish the classification model to identify these three emotions. Experimental results show this model works very well, and time-frequency features are effective in characterizing and recognizing emotions for this non-contact gait data. In particular, by the optimization algorithm, the recognition accuracy can be further averagely improved by about 13.7 percent.
KeywordEmotion gait joints Microsoft Kinect time-frequency analysis discrete fourier transform
DOI10.1109/TAFFC.2016.2637343
Indexed BySCI
Language英语
Funding OrganizationNSFC ; National High-tech RD Program of China ; National Basic Research Program of China (973 Program) ; Key Research Program of CAS
Funding Project[XDA06030800] ; Key Research Program of CAS[KJZD-EW-L04] ; National Basic Research Program of China (973 Program)[2014CB744600] ; National High-tech RD Program of China[2013AA01A606] ; NSFC[11301504] ; NSFC[11301504] ; National High-tech RD Program of China[2013AA01A606] ; National Basic Research Program of China (973 Program)[2014CB744600] ; Key Research Program of CAS[KJZD-EW-L04] ; [XDA06030800]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000451918200015
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS KeywordRECOGNITION
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/27832
Collection社会与工程心理学研究室
Corresponding AuthorLi, Baobin
Affiliation1.Univ Chinese Acad Sci, Sch Comp & Control, Beijing 100190, Peoples R China
2.China Elect Corp, Res Inst 6, Beijing 100083, Peoples R China
3.Chinese Acad Sci, Inst Psychol, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Li, Baobin,Zhu, Changye,Li, Shun,et al. Identifying Emotions from Non-Contact Gaits Information Based on Microsoft Kinects[J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,2018,9(4):585-591.
APA Li, Baobin,Zhu, Changye,Li, Shun,&Zhu, Tingshao.(2018).Identifying Emotions from Non-Contact Gaits Information Based on Microsoft Kinects.IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,9(4),585-591.
MLA Li, Baobin,et al."Identifying Emotions from Non-Contact Gaits Information Based on Microsoft Kinects".IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 9.4(2018):585-591.
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