Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models

A. Youn Park, Seong Whan Lee

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

5 Citations (Scopus)

Abstract

Gestures are expressive and meaningful body motions used in daily life as a means of communication so many researchers have aimed to provide natural ways for human-computer interaction through automatic gesture recognition. However, most of researches on recognition of actions focused mainly on sign gesture. It is difficult to directly extend to recognize whole body gesture. Moreover, previous approaches used manually segmented image sequences. This paper focuses on recognition and segmentation of whole body gestures, such as walking, running, and sitting. We introduce the gesture spotting algorithm that calculates the likelihood threshold of an input pattern and provides a confirmation mechanism for the provisionally matched gesture pattern. In the proposed gesture spotting algorithm, the likelihood of non-gesture Hidden Markov Models(HMM) can be used as an adaptive threshold for selecting proper gestures. The proposed method has been tested with a 3D motion capture data, which are generated with gesture eigen vector and Gaussian random variables for adequate variation. It achieves an average recognition rate of 98.3% with six consecutive gestures which contains non-gestures.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages100-111
Number of pages12
Volume3881 LNAI
DOIs
Publication statusPublished - 2006 Jul 7
Event6th International Gesture Workshop, GW 2005 - Berder Island, France
Duration: 2005 May 182005 May 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3881 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Gesture Workshop, GW 2005
CountryFrance
CityBerder Island
Period05/5/1805/5/20

Fingerprint

Gestures
Metrorrhagia
Hidden Markov models
Gesture
Markov Model
Gesture recognition
Human computer interaction
Random variables
Data acquisition
Communication
Likelihood
Adaptive Threshold
Gesture Recognition
Motion Capture
Image Sequence
Running
Consecutive
Walking
Segmentation
Random variable

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Park, A. Y., & Lee, S. W. (2006). Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3881 LNAI, pp. 100-111). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3881 LNAI). https://doi.org/10.1007/11678816_12

Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models. / Park, A. Youn; Lee, Seong Whan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3881 LNAI 2006. p. 100-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3881 LNAI).

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

Park, AY & Lee, SW 2006, Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3881 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3881 LNAI, pp. 100-111, 6th International Gesture Workshop, GW 2005, Berder Island, France, 05/5/18. https://doi.org/10.1007/11678816_12
Park AY, Lee SW. Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3881 LNAI. 2006. p. 100-111. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11678816_12
Park, A. Youn ; Lee, Seong Whan. / Gesture spotting in continuous whole body action sequences using discrete Hidden Markov models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3881 LNAI 2006. pp. 100-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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