Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
527005 | Image and Vision Computing | 2015 | 16 Pages |
•Formalization of object re-identification problem in a distributed environment•Re-identification treated as an open-world problem•Novelty detection and forgetting included in the scheme•A set of performance measures, geared towards open-world, distributed surveillance•Experiments on a many-camera (36) surveillance dataset and publicly available source code
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.
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