[1]XIAO Feng,ZHOU Jie.Human pose estimation in static images based on region segmentation and Monte Carlo sampling[J].CAAI Transactions on Intelligent Systems,2011,6(1):38-43.
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Human pose estimation in static images based on region segmentation and Monte Carlo sampling

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 1 Page number: 38-43 Column: 学术论文—机器感知与模式识别 Public date: 2011-02-25
Title:
Human pose estimation in static images based on region segmentation and Monte Carlo sampling
Author(s):
XIAO Feng;  ZHOU Jie
Department of Automation, Tsinghua University, Beijing 100084, China
Keywords:
static images;  human pose estimation;  region segmentation;  Monte Carlo sampling;  belief propagation
CLC:
TP391.4
DOI:
-
Abstract:
Human pose estimation in static images is one of the important issues in the field of image analysis in recent years. The main difficulties are that there’s less available information in static image, besides, there’re figure distortion due to multiple joints, change in clothes, background disturbance and shading, etc., which make the problem challenging. Aiming at the deficiency of existing algorithm, a new algorithm was proposed for human pose estimation in static images based on region segmentation, belief propagation and MonteCarlo sampling, in which foreground region segmentation was incorporated into the pose estimation, nontree constraints were introduced in the probabilistic graphical model, and MonteCarlo sampling was utilized to carry out probabilistic inference. Experimental results demonstrate that the proposed algorithm performs better on a common database compared with classical algorithm, producing a more precise estimate result and reducing 25% running time.
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