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This paper describes an approach to human action recognition based on the probabilistic optimization model of body parts using Hidden Markov Model (HMM). Our proposed method is able to distinguish between similar actions by only considering the body parts having major contribution to the actions, for example, legs for walking, jogging and running; hands for boxing, waving and clapping. We apply HMMs to model the stochastic movement of the body-parts for action recognition. The HMM constructiondoi:10.1111/j.1468-0394.2011.00610.x fatcat:x6ermka5pve2tih3syfoilz2fm