Recognition of emotions using Kinects

Institute of Psychology,Chinese Academy of Sciences, Beijing, China
The 6th Research Institute of China Electronics Corporation, Beijing, China
School of Computer and Control, University of Chinese Academy of Sciences, Beijing, China
Institute of Computing Technology,Chinese Academy of Sciences, Beijing, China
DOI
10.7287/peerj.preprints.1419v2
Subject Areas
Kinesiology, Psychiatry and Psychology
Keywords
emotion recognition, Microsoft Kinect, gait patterns
Copyright
© 2015 Li et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Li S, Cui L, Zhu C, Zhao N, Li B, Zhu T. 2015. Recognition of emotions using Kinects. PeerJ PrePrints 3:e1419v2

Abstract

Emotion recognition can improve the quality of patient care, product development and human-machine interaction.Psychological studies indicate that emotional state can be expressed in the way people walk,and the human gait can be used to reveal a person's emotional state.This paper proposes a novel method to do emotion recognition by using Microsoft Kinect to record gait patterns and train machine learning algorithms for emotion recognition. 59 subjects are recruited, and their gait patterns are recorded by two Kinect cameras.Joint selection, coordinate system transformation, sliding window gauss filtering,differential operation, and data segmentation are used for data preprocessing.We run Fourier transformation to extract features from the gait patterns and utilize Principal Component Analysis(PCA) for feature selection. By using NaiveBayes, RandomForests, LibSVM and SMO classifiers, the accuracy of recognition between natural and angry emotions can reach 80%,and the accuracy of recognition between natural and happy emotions can reach above 70%.The result indicates that Kinect can be used in the recognition of emotions with fairly well performance.

Author Comment

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Supplemental Information

Figure 1:The description of the experiment environment

DOI: 10.7287/peerj.preprints.1419v2/supp-1

Figure 2:The scene of the experiment environment

DOI: 10.7287/peerj.preprints.1419v2/supp-2

Figure 3:Stick figure and location of body joint centers estimated by Kinect

DOI: 10.7287/peerj.preprints.1419v2/supp-3

Figure 4:Kinect 3D coordinate

DOI: 10.7287/peerj.preprints.1419v2/supp-4

59 subjects'gait patterns in two-round experiments on two Kinects

DOI: 10.7287/peerj.preprints.1419v2/supp-5