Recognition of emotions using Kinects
Author and article information
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.
Cite this as
2015. Recognition of emotions using Kinects. PeerJ PrePrints 3:e1419v2 https://doi.org/10.7287/peerj.preprints.1419v2Author comment
This version contains a new file.
Sections
Supplemental Information
Figure 1:The description of the experiment environment
Figure 2:The scene of the experiment environment
Figure 3:Stick figure and location of body joint centers estimated by Kinect
59 subjects'gait patterns in two-round experiments on two Kinects
Additional Information
Competing Interests
The authors declare that they have no competing interests
Author Contributions
Shun Li conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Liqing Cui conceived and designed the experiments, performed the experiments, reviewed drafts of the paper.
Changye Zhu performed the experiments, analyzed the data.
Nan Zhao reviewed drafts of the paper.
Baobin Li conceived and designed the experiments.
Tingshao Zhu conceived and designed the experiments, reviewed drafts of the paper.
Ethics
The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers):
Institute of Psychology, Chinese Academy of Sciences H15010
Funding
Support was provided by the National High-tech R&D Program of China (2013AA01A606), National Basic Research Program of China(2014CB744600), Key Research Program of Chinese Academy of Sciences(CAS)(KJZDEWL04), and CAS Strategic Priority Research Program (XDA06030800). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
