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2016 | OriginalPaper | Buchkapitel

Dictionary Co-Learning for Multiple-Shot Person Re-Identification

verfasst von : Yang Wu, Dong Yang, Ru Zhou, Dong Wang

Erschienen in: Biometric Recognition

Verlag: Springer International Publishing

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Abstract

Person re-identification concerns about identifying people across cameras using full-body appearance in a non-obtrusive way for video surveillance and other commercial applications, for which it is usually hard or even impossible to get other more reliable biometric data. In this paper, we present a novel approach for multiple-shot person re-identification when multiple images or video frames are available for each person, which is usually the case in real applications. Our approach collaboratively learns camera-specific dictionaries and utilizes the efficient \(l_2\)-norm based collaborative representation for coding, which has shown great superiority in terms of both effectiveness and efficiency to all related existing models.

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Metadaten
Titel
Dictionary Co-Learning for Multiple-Shot Person Re-Identification
verfasst von
Yang Wu
Dong Yang
Ru Zhou
Dong Wang
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46654-5_74