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Reidentification of Persons Using Clothing Features in Real-Life Video
https://tokushima-u.repo.nii.ac.jp/records/2006915
https://tokushima-u.repo.nii.ac.jp/records/2006915dac2ad5a-fe7a-4c50-8304-1634b68a484e
名前 / ファイル | ライセンス | アクション |
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Item type | 文献 / Documents(1) | |||||||||||||||||||||||||||
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公開日 | 2019-11-14 | |||||||||||||||||||||||||||
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アクセス権 | open access | |||||||||||||||||||||||||||
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資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||||||||||
資源タイプ | journal article | |||||||||||||||||||||||||||
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識別子タイプ | DOI | |||||||||||||||||||||||||||
関連識別子 | https://doi.org/10.1155/2017/5834846 | |||||||||||||||||||||||||||
言語 | ja | |||||||||||||||||||||||||||
関連名称 | 10.1155/2017/5834846 | |||||||||||||||||||||||||||
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出版タイプ | VoR | |||||||||||||||||||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||||||||||
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タイトル | Reidentification of Persons Using Clothing Features in Real-Life Video | |||||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||||||
著者 |
Zhang, Guodong
× Zhang, Guodong
× Jiang, Peilin
× 松本, 和幸
WEKO
311
× 吉田, 稔
WEKO
641
× 北, 研二
WEKO
94
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内容記述タイプ | Abstract | |||||||||||||||||||||||||||
内容記述 | Person reidentification, which aims to track people across nonoverlapping cameras, is a fundamental task in automated video processing. Moving people often appear differently when viewed from different nonoverlapping cameras because of differences in illumination, pose, and camera properties. The color histogram is a global feature of an object that can be used for identification. This histogram describes the distribution of all colors on the object. However, the use of color histograms has two disadvantages. First, colors change differently under different lighting and at different angles. Second, traditional color histograms lack spatial information. We used a perception-based color space to solve the illumination problem of traditional histograms. We also used the spatial pyramid matching (SPM) model to improve the image spatial information in color histograms. Finally, we used the Gaussian mixture model (GMM) to show features for person reidentification, because the main color feature of GMM is more adaptable for scene changes, and improve the stability of the retrieved results for different color spaces in various scenes. Through a series of experiments, we found the relationships of different features that impact person reidentification. | |||||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||||||
書誌情報 |
en : Applied Computational Intelligence and Soft Computing 巻 2017, p. 5834846, 発行日 2017-01-11 |
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収録物識別子タイプ | ISSN | |||||||||||||||||||||||||||
収録物識別子 | 16879724 | |||||||||||||||||||||||||||
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収録物識別子タイプ | ISSN | |||||||||||||||||||||||||||
収録物識別子 | 16879732 | |||||||||||||||||||||||||||
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出版者 | Hindawi | |||||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||||||
権利情報 | ||||||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||||||
権利情報 | © 2017 Guodong Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | |||||||||||||||||||||||||||
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識別子 | 322039 | |||||||||||||||||||||||||||
識別子タイプ | URI | |||||||||||||||||||||||||||
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言語 | eng |