Early recognition based on co-occurrence of gesture patterns

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

2 Citations (Scopus)

Abstract

We propose an approach to achieve early recognition of gesture patterns. We assume that there are two people who interact with a machine, a robot or something. In such a situation, a gesture of a person often has a relationship with a gesture of another person. We exploit such a relationship to realize early recognition of gesture patterns. Early recognition is a method to recognize sequential patterns at their beginning parts. Therefore, in the case of gesture recognition, we can get a recognition result of human gestures before the gestures have finished. Recent years, some approaches have been proposed. In this paper, we expand the application range of early recognition to multiple people based on the co-occurrence of gesture patterns. In our approach, we use Self-Organizing Map to represent gesture patterns of each person, and associative memory based approach learns the relationship between co-occurring gestures. In the experiments, we have found that our proposed method achieved the early recognition more accurately and earlier than the traditional approach.

Original languageEnglish
Title of host publicationNeural Information Processing
Subtitle of host publicationModels and Applications - 17th International Conference, ICONIP 2010, Proceedings
Pages431-438
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2010
Event17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia
Duration: Nov 22 2010Nov 25 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6444 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Conference on Neural Information Processing, ICONIP 2010
CountryAustralia
CitySydney, NSW
Period11/22/1011/25/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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