Recognizing human action in time-sequential images using hidden Markov model

J. Yamato, Jun Ohya, K. Ishii

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

911 Citations (Scopus)

Abstract

A human action recognition method based on a hidden Markov model (HMM) is proposed. It is a feature-based bottom-up approach that is characterized by its learning capability and time-scale invariability. To apply HMMs, one set of time-sequential images is transformed into an image feature vector sequence, and the sequence is converted into a symbol sequence by vector quantization. In learning human action categories, the parameters of the HMMs, one per category, are optimized so as to best describe the training sequences from the category. To recognize an observed sequence, the HMM which best matches the sequence is chosen. Experimental results for real time-sequential images of sports scenes show recognition rates higher than 90%. The recognition rate is improved by increasing the number of people used to generate the training data, indicating the possibility of establishing a person-independent action recognizer.

Original languageEnglish
Title of host publicationProceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Pages379-385
Number of pages7
ISBN (Electronic)0818628553
DOIs
Publication statusPublished - 1992 Jan 1
Externally publishedYes
Event1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992 - Champaign, United States
Duration: 1992 Jun 151992 Jun 18

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1992-June
ISSN (Print)1063-6919

Conference

Conference1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992
CountryUnited States
CityChampaign
Period92/6/1592/6/18

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Yamato, J., Ohya, J., & Ishii, K. (1992). Recognizing human action in time-sequential images using hidden Markov model. In Proceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 379-385). [223161] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1992-June). IEEE Computer Society. https://doi.org/10.1109/CVPR.1992.223161