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A cloud computing architecture for characterization and classification of moving object

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Abstract

Video surveillance big data contains a great deal of information about moving objects. Multi moving object characterization and classification methods is the main characteristics to find a suitable description of the scene in all kinds of sports objects, features and match unknown similarity between moving objects. This paper presents a calculation of all the moving objects in the scene using cloud computing architecture with invariant moment value weighting method, combined with the invariant moments as the input parameter value, the establishment of multi-class classification model for multiple moving object classification. Experimental results show that this method can effectively improve the recognition rate of the moving object.

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Acknowledgments

This research has partially been supported by the project funded of the Department of Transportation Informatization under Grant No. 2013-364-836-900, Key Project of Jiangsu for Research and Development under Grant No. BE2015137, National Natural Science Foundation of China under Grant No. 71573107, 41374129, 41474095, 60673190 and 61203244, College Natural Science Research of Jiangsu Province under Grant No. 14KJB520008, Senior Technical Personnel of Scientific Research Fund of Jiangsu University under Grant No. 13JDG126, Research Innovation Program for College Graduates of Jiangsu Province under Grant No. KYLX15_1078, Basic research project of science and technology research and Development Fund of Shenzhen under Grand No. JCYJ20150401092136087.

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Authors and Affiliations

  1. Affiliated Hospital of Jiangsu University, Jiangsu University, Jiefang Road No. 438, Zhenjiang, Jiangsu, 212001, China

    Xiao-jun Chen

  2. School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China

    Xiao-jun Chen, Jia Ke, Tian-ming Zhan & Yong-zhao Zhan

  3. School of management, Jiangsu University, Zhenjiang, China

    Jia Ke, Wen-xin Wang & Xin-ping Song

  4. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China

    Xiao-bo Chen

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  1. Xiao-jun Chen
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  2. Jia Ke
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  3. Tian-ming Zhan
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  4. Wen-xin Wang
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  5. Yong-zhao Zhan
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  6. Xiao-bo Chen
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  7. Xin-ping Song
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Correspondence to Xiao-jun Chen.

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Chen, Xj., Ke, J., Zhan, Tm. et al. A cloud computing architecture for characterization and classification of moving object. Multimed Tools Appl 76, 17319–17336 (2017). https://doi.org/10.1007/s11042-016-4086-7

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  • DOI: https://doi.org/10.1007/s11042-016-4086-7

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