Recognition of manipulation sequences by human hand based on Support Vector Machine

Kazuya Matsuo, Kouji Murakami, Tsutomu Hasegawa, Ryo Kurazume

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a method of recognizing a manual task executed by a human hand by using the Support Vector Machine (SVM). We define several task states which are segmented from the continuous motion of human fingers in the context of an object manipulation. Based on margins of SVMs, the method constructs a binary decision tree which most effectively classifies and symbolizes the task state from joint angle trajectories of human fingers as input. The binary decision tree constructed by our method has been evaluated through experiments of recognizing the task states during a valve manipulation.

Original languageEnglish
Title of host publicationProceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
Pages2801-2806
Number of pages6
DOIs
Publication statusPublished - Dec 1 2007
Event33rd Annual Conference of the IEEE Industrial Electronics Society, IECON - Taipei, Taiwan, Province of China
Duration: Nov 5 2007Nov 8 2007

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
CountryTaiwan, Province of China
CityTaipei
Period11/5/0711/8/07

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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