The Survey of Big Data Problems in the Video Surveillance System

Xin Wang, Zheng Xu, Jie Dai

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.

References

  1. Liu,Y., Zhu,Y., Ni, Lionel M., and Xue, G. 2011. A Reliability-Oriented Transmission Service in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 22(12): 2100-2107.
  2. Liu, Y., Zhang, Q., and Ni, Lionel M. 2010. OpportunityBased Topology Control in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 21(3): 405-416.
  3. Hu, C., Xu, Z. et al. 2014. Semantic Link Network based Model for Organizing Multimedia Big Data. IEEE Transactions on Emerging Topics in Computing, 2(3):376-387.
  4. Luo, X., Xu, Z., Yu, J., and Chen, X. 2011. Building Association Link Network for Semantic Link on Web Resources. IEEE transactions on automation science and engineering, 8(3):482-494.
  5. Xu, Z. et al. 2015. Knowle: a Semantic Link Network based System for Organizing Large Scale Online News Events. Future Generation Computer Systems, 43-44:40-50.
  6. Xu, Z., Luo, X., Zhang, S., Wei, X., Mei, L., and Hu, C. 2014. Mining Temporal Explicit and Implicit Semantic Relations between Entities using Web Search Engines. Future Generation Computer Systems, 37:468-477.
  7. Zh, H., et al. 2010. Video Structured Description: A Novel Solution for Visual Surveillance. Lecture Notes in Computer Science, Volume 6298:629-636.
  8. Zh, T., Liu, S., Xu, C., Lu, H. 2012. Mining Semantic Context Information for Intelligent Video Surveillance of Traffic Scenes Industrial Informatics. IEEE Transactions on Volume:9 , Issue: 1 :149 - 160.
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Paper Citation


in Harvard Style

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 - Volume 1: ISME, ISBN 978-989-758-163-2, pages 126-129. DOI: 10.5220/0006020301260129


in Bibtex Style

@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 - Volume 1: ISME,},
year={2015},
pages={126-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006020301260129},
isbn={978-989-758-163-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Information Science and Management Engineering III - Volume 1: 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