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A new method for human action recognition: Discrete HMM with improved LBG algorithm

  • Zhongxin Qu*
  • , Tingshu Lu
  • , Xiaojiong Liu
  • , Qianqian Wu
  • , Mingjiang Wang
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Hidden Markov Model (HMM) algorithm and Vector Quantization (VQ) algorithm are widely used in the field of speech recognition. The innovation of this paper will be the introduction of the above two algorithms into human action recognition and making them as a solution to recognize action of the continuous multi frames video. Simulated Annealing algorithm and the empty cavity processing algorithm improve vector quantization algorithm and obtain the global optimal codebook. The recognition result of the new algorithm is much better than the original algorithm and traditional algorithms. The new method realizes the identification of abnormal behavior.

Original languageEnglish
Title of host publicationProceedings of 2015 IEEE 9th International Conference on Anti-Counterfeiting, Security and Identification, ASID 2015
PublisherIEEE Computer Society
Pages109-113
Number of pages5
ISBN (Electronic)9781467371391
DOIs
StatePublished - 11 Feb 2016
Externally publishedYes
Event9th IEEE International Conference on Anti-Counterfeiting, Security and Identification, ASID 2015 - Xiamen, China
Duration: 25 Sep 201527 Sep 2015

Publication series

NameProceedings of the International Conference on Anti-Counterfeiting, Security and Identification, ASID
Volume2016-February
ISSN (Print)2163-5048
ISSN (Electronic)2163-5056

Conference

Conference9th IEEE International Conference on Anti-Counterfeiting, Security and Identification, ASID 2015
Country/TerritoryChina
CityXiamen
Period25/09/1527/09/15

Keywords

  • HMM
  • LBG
  • action recognition
  • codebook
  • empty cavity split
  • simulated annealing
  • vector quantitation

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