KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Statistical and Entropy Based Human Motion Analysis

  • Lee, Chin-Poo (Faculty of Information Science and Technology, Multimedia University) ;
  • Woon, Wei-Lee (Information Technology Program, Masdar Institute of Science and Technology) ;
  • Lim, Kian-Ming (Faculty of Information Science and Technology, Multimedia University)
  • Received : 2010.07.13
  • Accepted : 2010.10.27
  • Published : 2010.12.23
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Abstract

As visual surveillance systems gain wider usage in a variety of fields, it is important that they are capable of interpreting scenes automatically, also known as "human motion analysis" (HMA). However, existing HMA methods are too domain specific and computationally expensive. This paper proposes a general purpose HMA method that is based on the idea that human beings tend to exhibit erratic motion patterns during abnormal situations. Limb movements are characterized using the statistics of angular and linear displacements. In addition, the method is enhanced via the use of the entropy of the Fourier spectrum to measure the randomness of subject's motions. Various experiments have been conducted and the results indicate that the proposed method has very high classification accuracy in identifying anomalous behavior.

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References

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