Joint person re-identification and camera network topology inference in hock for multiple cameras

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In this study, we propose a unified framework which jointly solves both person re-identification and camera network topology inference problems with minimal prior knowledge about the environments. The proposed framework takes general multi-camera network environments into account and can be applied to online person re-identification in large-scale multi-camera networks. In addition, to show the superiority of the proposed framework, we provide a new person re-identification dataset with full annotations, named SLP, captured in the multi-camera network. Experimental results using our re-identification and public datasets show that the proposed methods are promising for both person re-identification and camera topology inference tasks.
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
Issue Date
2019-03
Language
English
Article Type
Article
Citation

COMPUTER VISION AND IMAGE UNDERSTANDING, v.180, pp.34 - 46

ISSN
1077-3142
DOI
10.1016/j.cviu.2019.01.003
URI
http://hdl.handle.net/10203/261496
Appears in Collection
ME-Journal Papers(저널논문)
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