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An Ensemble Classifier Based on Three-Way Decisions for Social Touch Gesture Recognition

  • Gangqiang ZhangEmail author
  • Qun Liu
  • Yubin Shi
  • Hongying Meng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10942)

Abstract

Touch is an important form of social interaction. In Human Robot Interaction (HRI), touch can provide additional information to other modalities, such as audio, visual. In this paper, an ensemble classifier based on three-way decisions is proposed to recognize touch gestures. Firstly, features are extracted from six perspectives and four classifiers are constructed on different scales with different preprocessing methods. Then an ensemble classifier is used to combine the four classifiers to classify touch gestures. Our method is tested on the public Corpus of Social Touch (CoST) dataset. The experiment results not only verify the validity of our method but also show a better performance of our ensemble classifier.

Keywords

Touch gesture recognition Data preprocessing Ensemble classifier Three-way decisions 

Notes

Acknowledgments

The work is supported by the Key Research and Development Program of Chongqing (cstc2017zdcy-zdyfx0091) and the Key Research and Development Program on AI of Chongqing (cstc2017rgzn-zdyfx0022) and the National Nature Science Foundation of China (61572091).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Gangqiang Zhang
    • 1
    Email author
  • Qun Liu
    • 1
  • Yubin Shi
    • 1
  • Hongying Meng
    • 2
  1. 1.Chongqing Key Laboratory of Computational IntelligenceChongqing University of Posts and TelecommunicationsChongqingPeople’s Republic of China
  2. 2.Department of Electronic and Computer EngineeringBrunel University LondonUxbridgeUK

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