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Authors: Xin Wang ; Zheng Xu and Jie Dai

Affiliation: The Third Research Institute of the Ministry of Public Security, China

Keyword(s): Big data, Video intelligent analysis, Video structured description, Repository database, Cloud computing.

Abstract: Video surveillance has become the main tool due to its rich, intuitive and accurate information. However, with the large-scale construction of video surveillance systems all over the world, problems such as “useful information and clues cannot be found immediately with video big data” decrease detecting efficiency during crime prediction and public security governance. This paper examines the current techniques including video intelligent analysis and video structured description (VSD), knowledge discovery in database, and cloud computing including virtualization, distributed computing and storage, and proposes a framework of the next generation video surveillance system to explain how to discovery knowledge from video big data, organize and manage massive heterogeneous resources, and provide operating environment and resources for tasks, for the purpose of supporting police to predict crime quickly and efficiently.

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Paper citation in several formats:
Wang, X.; Xu, Z. and Dai, J. (2015). The Survey of Big Data Problems in the Video Surveillance System. In Proceedings of the Information Science and Management Engineering III - ISME; ISBN 978-989-758-163-2, SciTePress, pages 126-129. DOI: 10.5220/0006020301260129

@conference{isme15,
author={Xin Wang. and Zheng Xu. and Jie Dai.},
title={The Survey of Big Data Problems in the Video Surveillance System},
booktitle={Proceedings of the Information Science and Management Engineering III - ISME},
year={2015},
pages={126-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006020301260129},
isbn={978-989-758-163-2},
}

TY - CONF

JO - Proceedings of the Information Science and Management Engineering III - ISME
TI - The Survey of Big Data Problems in the Video Surveillance System
SN - 978-989-758-163-2
AU - Wang, X.
AU - Xu, Z.
AU - Dai, J.
PY - 2015
SP - 126
EP - 129
DO - 10.5220/0006020301260129
PB - SciTePress