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- W2912488224 abstract "Appearance-based person re-identification (PRID) is currently an active and challenging research topic. Recently proposed approaches have mostly dealt with low- and middle-level processing of images. Furthermore, there is very limited research that has focused on view information. View variation limits the performance of most approaches because a person’s appearance from one view can be completely different from that of another view, which makes the re-identification challenging. In this work, we study the influence of the view on PRID and propose several fusion strategies that utilize multi-view information to handle the PRID problem. We perform experiments on a re-mapped version of Market-1501 dataset and an internal dataset. Our proposed multi-view strategy increases the recognition rate at rank-one by a large margin in comparison with that obtained via random view matching or multi-shot." @default.
- W2912488224 created "2019-02-21" @default.
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- W2912488224 date "2019-01-01" @default.
- W2912488224 modified "2023-09-26" @default.
- W2912488224 title "View-Aware Person Re-identification" @default.
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- W2912488224 doi "https://doi.org/10.1007/978-3-030-12939-2_4" @default.
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