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| Human Pose Model and Block Growth Combined Crowd Segmentatio |
| Deng Ying-na; Zhu Hong; Liu Wei; Zhang Xiao-dan |
| College of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048 China |
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Abstract Crowd object segmentation is a key issue of the object tracking and recognition in multiple cameras. Human rough models with position, scale and pose information are constructed and then get the corresponding models by using Bayesian model. Then, the foreground is segmented into blocks of similar color distribution. Then the problem of the seed blocks selection is solved thought of color and position information under human inter-occlusion, and human region is received by seed growth. For blocks with similar color, they are merged into the objects by comparing the edge energy they brought. It can be seen that the method could segment the crowd precisely, and is not sensitive to background noise from the experimental results.
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Received: 21 January 2009
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Corresponding Authors:
Deng Ying-na
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2010, Vol. 32 
