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Camera Selection in Far-Field Video Surveillance Networks

Kaimin CHEN, Wei LI, Zhaohuan ZHAN, Binbin LIANG, Songchen HAN

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Summary :

Since camera networks for surveillance are becoming extremely dense, finding the most informative and desirable views from different cameras are of increasing importance. In this paper, we propose a camera selection method to achieve the goal of providing the clearest visibility possible and selecting the cameras which exactly capture targets for the far-field surveillance. We design a benefit function that takes into account image visibility and the degree of target matching between different cameras. Here, visibility is defined using the entropy of intensity histogram distribution, and the target correspondence is based on activity features rather than photometric features. The proposed solution is tested in both artificial and real environments. A performance evaluation shows that our target correspondence method well suits far-field surveillance, and our proposed selection method is more effective at identifying the cameras that exactly capture the surveillance target than existing methods.

Publication
IEICE TRANSACTIONS on Communications Vol.E102-B No.3 pp.528-536
Publication Date
2019/03/01
Publicized
2018/08/29
Online ISSN
1745-1345
DOI
10.1587/transcom.2018EBP3079
Type of Manuscript
PAPER
Category
Network

Authors

Kaimin CHEN
  Sichuan University
Wei LI
  Sichuan University
Zhaohuan ZHAN
  Sichuan University
Binbin LIANG
  Sichuan University
Songchen HAN
  Sichuan University

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