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Selecting Effective and Discriminative Spatio-Temporal Interest Points for Recognizing Human Action
ZHANG Hongbo 1,LI Shaozi 2 *,SU Songzhi 3 #
1.School of Information Science and Technology, Xiamen University, FuJian XiaMen 361005
2. Fujian Key Laboratory of the Brain-like Intelligent Systems (Xiamen University), Xiamen, China, 361005
3.School of Information Science and Technology, Xiamen University, China, 361005
*Correspondence author
#Submitted by
Subject:
Funding: the Shenzhen Science and Technology Research Foundation(No.No. JC200903180630A and ZYB200907110169A), the National Nature Science Foundation of China(No.No. 61202143), the Doctoral Program Foundation of Institutions of Higher Education of China (No.No. 20090121110032)
Opened online: 5 November 2012
Accepted by: none
Citation: ZHANG Hongbo,LI Shaozi,SU Songzhi.Selecting Effective and Discriminative Spatio-Temporal Interest Points for Recognizing Human Action[OL]. [ 5 November 2012] http://en.paper.edu.cn/en_releasepaper/content/4493196
 
 
Many successful methods for recognizing human action are spatio-temporal interest point (STIP) based methods. Given a test video sequence, for matching-based method using voting mechanism, each test STIP casts a vote for each action class based on its mutual information with respect to the respective class, which is measured in terms of class likelihood probability. Therefore, two issues should be addressed to improve the accuracy of action recognition. First, effective STIPs in the training set must be selected as references for accurately estimating probability. Second, discriminative STIPs in test set must be selected for voting. This work uses e-nearest neighbors as effective STIPs for estimating the class probability and uses a variance filter for selecting discriminative STIPs. Experimental results verify that the proposed method is more accurate than existing action recognition methods.paper.
Keywords:Artificial Intelligence; Human action recognition; discriminative power; class likelihood probability; variance filter.
 
 
 

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