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Semantic Based Annotation for Surveillance Big Data Using Domain Knowledge

Author

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  • Feng Xie

    (Jiangsu University of Technology, Changzhou, China)

  • Zheng Xu

    (The Third Research Institute of the Ministry of Public Security, Shanghai, China & Tsinghua University, Beijing, China)

Abstract

Video surveillance technology is playing a more and more important role in traffic detection. Vehicle's static properties are crucial information in examining criminal and traffic violations. Image and video resources play an important role in traffic events analysis. With the rapid growth of the video surveillance devices, large number of image and video resources is increasing being created. It is crucial to explore, share, reuse, and link these multimedia resources for better organizing traffic events. With the development of Video Surveillance technology, it has been wildly used in the traffic monitoring. Therefore, there is a trend to use Video Surveillance to do intelligent analysis on vehicles. Now, using software and tools to analyze vehicles in videos has already been used in smart cards and electronic eye, which helps polices to extract useful information like plate, speed, etc. And the key technology is to obtain various properties of the vehicle. This paper provides an overview of the algorithms and technologies used in extracting static properties of vehicle in the video.

Suggested Citation

  • Feng Xie & Zheng Xu, 2015. "Semantic Based Annotation for Surveillance Big Data Using Domain Knowledge," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 9(1), pages 16-29, January.
    • Handle: RePEc:igg:jcini0:v:9:y:2015:i:1:p:16-29
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