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Semantic enhanced cloud environment for surveillance data management using video structural description

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Abstract

Recently, the number of surveillance video data has grown enormously since the popularity of the smart cities, which brings the difficulties to users for searching and analyzing the content of the videos. These video data are not limited to data anymore, which provide the effective information for criminal investigation systems, intrusion detection system, and many others. However, as the number of available cloud services increases, the problem of data discovery and selection arises. The semantic technology is an effective choice for enhancing the accurate of the data searching and analyzing process. In this paper, a semantic based cloud environment is proposed to facilitate the analyzing and searching process of surveillance video data. An architecture integrating ontology building, semantic annotation, and semantic search is proposed to leverage the semantic description of the video data to find them from concept-based level. A semantic intermediate layer which organizes the video data based on their semantic relations is given. Moreover, the proposed method is used in the intelligent transportation field, which shows the bright prospect of the proposed method in real applications.

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Notes

  1. www.w3.org/RDF/, 2013.

  2. www.openstreetmap.org.

  3. www.opencv.org.

  4. www.virtuoso.com/, 2013.

  5. www.larkc.eu/, 2013.

  6. The 215 illegal traffic events are get from www.shjtaq.com/zwfg/dmb2012.htm.

  7. http://protege.stanford.edu/, 2013.

  8. www.docjar.org, 2013.

  9. www.w3.org/Submission/SWRL/, 2013.

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Acknowledgments

This work was supported in part by the National Science and Technology Major Project under Grant 2013ZX01033002-003, in part by the National High Technology Research and Development Program of China (863 Program) under Grant 2013AA014601, 2013AA014603, in part by National Key Technology Support Program under Grant 2012BAH07B01, in part by the National Science Foundation of China under Grant 61300202, and in part by the Science Foundation of Shanghai under Grant 13ZR1452900.

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Authors and Affiliations

  1. The Third Research Institute of Ministry of Public Security, Shanghai, China

    Zheng Xu, Lin Mei, Yunhuai Liu, Chuanping Hu & Lan Chen

  2. Tsinghua University, Beijing, China

    Zheng Xu

Authors
  1. Zheng Xu
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  2. Lin Mei
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  3. Yunhuai Liu
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  4. Chuanping Hu
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  5. Lan Chen
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Correspondence to Zheng Xu.

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Xu, Z., Mei, L., Liu, Y. et al. Semantic enhanced cloud environment for surveillance data management using video structural description. Computing 98, 35–54 (2016). https://doi.org/10.1007/s00607-014-0408-7

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