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Research of unsupervised posture modeling and action recognition based on spatial-temporal interesting points

Journal Article


Abstract


  • Posture modeling is critical for action description and recognition,a posture modeling and action recognition method is proposed in this paper.Spatial Temporal Interesting Points (STIPs) are extracted from learning samples,in fact,one posture consists of a set of STIPs;a unsupervised clustering method is adopted to classify salient postures from these posture samples,then a GMM model is established for each clustering result;transitional probability among salient postures are calculated,and a Visible state Markov Model(VMM) is learnt to describe various actions.Bi-gram method is put forward for action recognition,Extensive experiments are conducted and the results prove its robustness and validity.

UOW Authors


  •   Wang, Chuanxu (external author)
  •   Liu, Yun (external author)
  •   Li, Wanqing

Publication Date


  • 2011

Citation


  • Wang, C., Liu, Y. & Li, W. (2011). Research of unsupervised posture modeling and action recognition based on spatial-temporal interesting points. Chinese Journal of Electronics, 39 (8), 1751-1756.

Scopus Eid


  • 2-s2.0-80053072126

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1948

Has Global Citation Frequency


Number Of Pages


  • 5

Start Page


  • 1751

End Page


  • 1756

Volume


  • 39

Issue


  • 8

Abstract


  • Posture modeling is critical for action description and recognition,a posture modeling and action recognition method is proposed in this paper.Spatial Temporal Interesting Points (STIPs) are extracted from learning samples,in fact,one posture consists of a set of STIPs;a unsupervised clustering method is adopted to classify salient postures from these posture samples,then a GMM model is established for each clustering result;transitional probability among salient postures are calculated,and a Visible state Markov Model(VMM) is learnt to describe various actions.Bi-gram method is put forward for action recognition,Extensive experiments are conducted and the results prove its robustness and validity.

UOW Authors


  •   Wang, Chuanxu (external author)
  •   Liu, Yun (external author)
  •   Li, Wanqing

Publication Date


  • 2011

Citation


  • Wang, C., Liu, Y. & Li, W. (2011). Research of unsupervised posture modeling and action recognition based on spatial-temporal interesting points. Chinese Journal of Electronics, 39 (8), 1751-1756.

Scopus Eid


  • 2-s2.0-80053072126

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1948

Has Global Citation Frequency


Number Of Pages


  • 5

Start Page


  • 1751

End Page


  • 1756

Volume


  • 39

Issue


  • 8