Learning deep features from body and parts for person re-identification in camera networks
Abstract In this paper, we propose to learn deep features from body and parts (DFBP) in camera networks which combine the advantages of part-based and body-based features. Specifically, we utilize subregion pairs to train the part-based feature learning model and predict whether they belong to posit...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
SpringerOpen
2018-03-01
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| Серии: | EURASIP Journal on Wireless Communications and Networking |
| Предметы: | |
| Online-ссылка: | http://link.springer.com/article/10.1186/s13638-018-1060-2 |
| Метки: |
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