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Video traffic analytics for large scale surveillance

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Abstract

The video traffic analysis is the most important issue for large scale surveillance. In the large scale surveillance system, huge amount of live digital video data is submitted to the storage servers through the number of externally connected scalable components. The system also contains huge amount of popular and unpopular old videos in the archived storage servers. The video data is delivered to the viewers, partly or completely on demand through a compact system. In real time, huge amount of video data is imported to the viewer’s node for various analysis purposes. The viewers use a number of interactive operations during the real time tracking suspect. The compact video on demand system is used in peer to peer mesh type hybrid architecture. The chunk of video objects move fast through the real time generated compact topological space. Video traffic analytics is required to transfer compressed multimedia data efficiently. In this work, we present a dynamically developed topological space, using mixed strategy by game approach to move the video traffic faster. The simulation results are well addressed in real life scenario.

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Acknowledgments

The authors are grateful to Sharmista Das Kanrar from Bishop Westcott, Ranchi, India.

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Authors and Affiliations

  1. Vehere Interactive Pvt Ltd, Calcutta, 700053, West Bengal, India

    Soumen Kanrar

  2. Department of Computer Science, Vidyasagar University, Midnapore, 721102, West Bengal, India

    Soumen Kanrar & Niranjan Kumar Mandal

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  1. Soumen Kanrar
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  2. Niranjan Kumar Mandal
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Correspondence to Soumen Kanrar.

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Kanrar, S., Mandal, N.K. Video traffic analytics for large scale surveillance. Multimed Tools Appl 76, 13315–13342 (2017). https://doi.org/10.1007/s11042-016-3752-0

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