Statistical and entropy based human motion analysis

Chin Poo Lee, Wei Lee Woon, Kian Ming Lim

Research output: Journal PublicationArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1194-1208
Number of pages15
JournalKSII Transactions on Internet and Information Systems
Issue number6
Publication statusPublished - Dec 2010
Externally publishedYes


  • Computer vision
  • Entropy
  • Image processing
  • Motion analysis
  • Neural networks

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


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