IEEJ Transactions on Electronics, Information and Systems
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
<Speech and Image Processing, Recognition>
Action Recognition and Suspicious Action Detection with Mixture Distributions of Action Primitives
Yoshio IwaiYasuhiro AokiHiroshi Ishiguro
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2010 Volume 130 Issue 4 Pages 546-556

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Abstract
In this paper, we propose a generic framework for detecting suspicious actions with mixture distributions of action primitives, of which collection represents human actions. The framework is based on Bayesian approach and the calculation is performed by Sequential Monte Carlo method, also known as Particle filter. Sequential Monte Carlo is used to approximate the distributions for fast calculation, but it tends to converge one local minimum. We solve that problem by using mixture distributions of action primitives. By this approach, the system can recognize people's actions as whether suspicious actions or not.
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© 2010 by the Institute of Electrical Engineers of Japan
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