Video traffic analytics for large scale surveillance

被引:0
|
作者
Soumen Kanrar
Niranjan Kumar Mandal
机构
[1] Vehere Interactive Pvt Ltd,Department of Computer Science
[2] Vidyasagar University,undefined
来源
Multimedia Tools and Applications | 2017年 / 76卷
关键词
Interactive session; Video on demand; Surveillance; Mixed strategy; Topology; Compact space; Mesh structure; Hybrid architecture;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:13315 / 13342
页数:27
相关论文
共 50 条
  • [41] FFS-VA: A Fast Filtering System for Large-scale Video Analytics
    Zhang, Chen
    Cao, Qiang
    Jiang, Hong
    Zhang, Wenhui
    Li, Jingjun
    Yao, Jie
    PROCEEDINGS OF THE 47TH INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, 2018,
  • [42] The future of video analytics for surveillance and its ethical implications
    Adams, Andrew A.
    Ferryman, James M.
    SECURITY JOURNAL, 2015, 28 (03) : 272 - 289
  • [43] Large-scale Video Analytics with Cloud-Edge Collaborative Continuous Learning
    Nan, Ya
    Jiang, Shiqi
    Li, Mo
    ACM TRANSACTIONS ON SENSOR NETWORKS, 2024, 20 (01)
  • [44] The future of video analytics for surveillance and its ethical implications
    Andrew A Adams
    James M Ferryman
    Security Journal, 2015, 28 : 272 - 289
  • [45] Precision large scale air traffic surveillance using IMM/assignment estimators
    Wang, H
    Kirubarajan, T
    Bar-Shalom, Y
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1999, 35 (01) : 255 - 266
  • [46] Video Analytics for Panning Camera in Dynamic Surveillance Environment
    Asif, Muhammad
    Soraghan, John
    PROCEEDINGS ELMAR-2008, VOLS 1 AND 2, 2008, : 79 - 82
  • [47] Scheduling Massive Camera Streams to Optimize Large-Scale Live Video Analytics
    Rong, Chenghao
    Wang, Jessie Hui
    Liu, Juncai
    Wang, Jilong
    Li, Fenghua
    Huang, Xiaolei
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2022, 30 (02) : 867 - 880
  • [48] Design and Implementation of vsStor: A Large-Scale Video Surveillance Storage System
    Liu, Guoliang
    Xu, Jianjun
    Feng, Yuanjing
    Lu, Guoquan
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA), 2018, : 356 - 362
  • [49] Target-Aware Camera Placement for Large-Scale Video Surveillance
    Wu, Hongxin
    Zeng, Qinghou
    Guo, Chen
    Zhao, Tiesong
    Chen, Chang Wen
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2024, 34 (12) : 13338 - 13348
  • [50] Efficient large-scale graph data optimization for intelligent video surveillance
    Shang, Quanhong
    Zhang, Shujun
    Wang, Yanbo
    Sun, Chen
    Wang, Zepeng
    Zhang, Luming
    2ND ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2017), 2017, 887