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- W2100028243 abstract "In this paper, we approach the task of appearance based person re-identification for scenarios where no biometric features can be used. For that, we build on a person re-identification approach that uses the Implicit Shape Model (ISM) and SIFT features for re-identification. This approach builds identity models of persons during tracking and employs these models for re-identification. We apply this re-identification, which was until now only evaluated in the infrared spectrum, to data acquired in the visible spectrum. Furthermore we evaluate view independence of the re-identification approach and introduce methods that extend view invariance. Specifically, we (i) propose a method for online view-determination of a tracked person, (ii) use the online view-determination to generate view specific identity models of persons which increase model distinctiveness in re-identification, and (iii) introduce a method to convert identity models between views to increase view independence." @default.
- W2100028243 created "2016-06-24" @default.
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- W2100028243 date "2011-08-01" @default.
- W2100028243 modified "2023-09-26" @default.
- W2100028243 title "View-invariant person re-identification with an Implicit Shape Model" @default.
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- W2100028243 doi "https://doi.org/10.1109/avss.2011.6027319" @default.
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