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    <title>Cameranetwork on ViCoS Lab</title>
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      <title>Visual re-identification across large, distributed camera networks</title>
      <link>/publications/kenk2015visual/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;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.&lt;/p&gt;</description>
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