Silhouette-based human pose estimation using reversible jump Markov chain Monte Carlo | Zendy

Shin-Shinh Huang | Zendy; LiChen Fu | Zendy; PeiYung Hsiao | Zendy

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Silhouette-based human pose estimation using reversible jump Markov chain Monte Carlo

Author(s) -

Shin-Shinh Huang,

LiChen Fu,

PeiYung Hsiao

Publication year - 2006

Publication title -

electronics letters

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.375

H-Index - 146

eISSN - 1350-911X

pISSN - 0013-5194

DOI - 10.1049/el:20060044

Subject(s) - reversible jump markov chain monte carlo , silhouette , markov chain monte carlo , markov chain , computer science , monte carlo method , jump , linear subspace , algorithm , inference , pose , artificial intelligence , mathematics , machine learning , geometry , statistics , physics , quantum mechanics

A novel approach for recovering the human body configuration based on the silhouette is presented. By considering pose inference as traversing the difference subspaces and using a data-driven mechanism, reversible jump Markov chain Monte Carlo (RJMCMC) can explore such solution space very efficiently. Experimental results are provided to demonstrate the efficiency and effectiveness of the proposed...

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