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Automatic Emotion Recognition Based on Non-Contact Gaits Information
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Author(s): Jingying Wang (University of Chinese Academy of Sciences, China), Baobin Li (University of Chinese Academy of Sciences, China), Changye Zhu (University of Chinese Academy of Sciences, China), Shun Li (University of Chinese Academy of Sciences, China)and Tingshao Zhu (University of Chinese Academy of Sciences, China)
Copyright: 2019
Pages: 14
Source title:
Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7368-5.ch005
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Abstract
Automatic emotion recognition was of great value in many applications; however, to fully display the application value of emotion recognition, more portable, non-intrusive, inexpensive technologies need to be developed. Except face expression and voices, human gaits could reflect the walker's emotional state too. By utilizing 59 participants' gaits data with emotion labels, the authors train machine learning models that are able to “sense” individual emotion. Experimental results show these models work very well and prove that gait features are effective in characterizing and recognizing emotions.
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