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Visual re-identification across large, distributed camera networks
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DOI：10.1016/j.imavis.2014.11.002.png)
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Abstract
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We propose a holistic approach to the problem of re-identification in an environment of distributed smart cameras. We model the re-identification process in a distributed camera network as a distributed multi-class classifier, composed of spatially distributed binary classifiers. We treat the problem of re-identification as an open-world problem, and address novelty detection and forgetting. As there are many tradeoffs in design and operation of such a system, we propose a set of evaluation measures to be used in addition to the recognition performance. The proposed concept is illustrated and evaluated on a new many-camera surveillance dataset and SAIVT-SoftBio dataset. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Re-identification
Distributed sensors
Smart cameras
Visual-sensor networks
Surveillance
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