Approach of Skeleton Pruning with Bayesian Model

Qin Hong-xing; Sun Ying

doi:10.11999/JEIT150003

Volume 37 Issue 9

Sep. 2015

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Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

Citation:

Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

Citation:

Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

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Approach of Skeleton Pruning with Bayesian Model

doi: 10.11999/JEIT150003

Qin Hong-xing¹,
Sun Ying¹

Received Date: 2015-01-05
Rev Recd Date: 2015-05-13
Publish Date: 2015-09-19

Abstract

Abstract

Considering the problem that most of the existing skeleton calculation methods exhibit extreme sensitivity to the shape noise, a Bayes based algorithm for the skeleton pruning is proposed . The algorithm models the skeleton and growth process with Bayesian statistics framework. Based on the model, an iterative optimization is performed to prune the candidate branches. Due to the fact that the existing reconstruction error can not evaluate the simplicity of skeletons well, a new concept called Effective Rate is proposed to make quantitative analysis on the pruned skeleton with taking the simplicity into consideration. The experiments show that the proposed algorithm is robust to the shape noise and acts better in simplifying the skeleton structure and representing shape accurately.

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References(22)

References

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