• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Statistical and Entropy Based Human Motion Analysis

Vol. 4, No.6, December 23, 2010
10.3837/tiis.2010.12.012, Download Paper (Free):

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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Cite this article

[IEEE Style]
Chin-Poo Lee, Wei-Lee Woon and Kian-Ming Lim, "Statistical and Entropy Based Human Motion Analysis," KSII Transactions on Internet and Information Systems, vol. 4, no. 6, pp. 1194-1208, 2010. DOI: 10.3837/tiis.2010.12.012

[ACM Style]
Lee, C., Woon, W., and Lim, K. 2010. Statistical and Entropy Based Human Motion Analysis. KSII Transactions on Internet and Information Systems, 4, 6, (2010), 1194-1208. DOI: 10.3837/tiis.2010.12.012