Human pose tracking recognition algorithm for monocular video was proposed to model human part parameters using video features combination with 3D motion capture data. Firstly three-dimensional data projection constraint graph structure was defined. To simplify the reasoning process, a constraint graph of the spanning tree construction algorithm and the balancing algorithm were proposed. Combination with the proposed function mechanism, spanning tree of constraint graph and Metropolis-Hastings method, human motion under monocular video can be tracking and recognition, inferring the 3D motion parameters. By using data-driven (Markov chain Monte Carlo MCMC) and constrain map, human motion limb recognition algorithm is proposed, and the method can be applied to data-driven online human behavior recognition. Experimental results show that the proposed method can recognize human motion action automatically and accurately in monocular video. © 2012 Springer Science+Business Media B.V.
CITATION STYLE
Ouyang, Y., & Xing, J. (2012). Human action recognition algorithm based on minimum spanning tree. In Lecture Notes in Electrical Engineering (Vol. 107 LNEE, pp. 871–879). https://doi.org/10.1007/978-94-007-1839-5_94
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