| ZHAO Qianqian (赵倩倩)*,WU Hanxiao*,HUANG Linhan **,ZHU Jianqing** ***,ZENG Huanqiang**.[J].高技术通讯(英文),2023,29(2):194~205 |
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| Visible-infrared person re-identification using query related cluster |
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| DOI：10. 3772/ j. issn. 1006-6748. 2023. 02. 010 |
| 中文关键词: |
| 英文关键词: query related cluster (QRC), cross-modality, visible-infrared person re-identification (VIPR), video surveillance |
| 基金项目: |
| Author Name | Affiliation | | ZHAO Qianqian (赵倩倩)* | (?College of Information Science and Engineering, Huaqiao University, Xiamen 361021, P. R. China)
(??College of Engineering, Huaqiao University, Quanzhou 362021, P. R. China)
(???Xiamen Yealink Network Technology Company Limited, Xiamen 361015, P. R. China) | | WU Hanxiao* | (?College of Information Science and Engineering, Huaqiao University, Xiamen 361021, P. R. China)
(??College of Engineering, Huaqiao University, Quanzhou 362021, P. R. China)
(???Xiamen Yealink Network Technology Company Limited, Xiamen 361015, P. R. China) | | HUANG Linhan ** | (?College of Information Science and Engineering, Huaqiao University, Xiamen 361021, P. R. China)
(??College of Engineering, Huaqiao University, Quanzhou 362021, P. R. China)
(???Xiamen Yealink Network Technology Company Limited, Xiamen 361015, P. R. China) | | ZHU Jianqing** *** | (?College of Information Science and Engineering, Huaqiao University, Xiamen 361021, P. R. China)
(??College of Engineering, Huaqiao University, Quanzhou 362021, P. R. China)
(???Xiamen Yealink Network Technology Company Limited, Xiamen 361015, P. R. China) | | ZENG Huanqiang** | (?College of Information Science and Engineering, Huaqiao University, Xiamen 361021, P. R. China)
(??College of Engineering, Huaqiao University, Quanzhou 362021, P. R. China)
(???Xiamen Yealink Network Technology Company Limited, Xiamen 361015, P. R. China) |
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| 中文摘要: |
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| 英文摘要: |
| Visible-infrared person re-identification (VIPR), is a cross-modal retrieval task that searches a target from a gallery captured by cameras of different spectrums. The severe challenge for VIPR is the large intra-class variation caused by the modal discrepancy between visible and infrared images. For that, this paper proposes a query related cluster (QRC) method for VIPR. Firstly, this paper uses an attention mechanism to calculate the similarity relation between a visible query and infrared images with the same identity in the gallery. Secondly, those infrared images with the same query images are aggregated by using the similarity relation to form a dynamic clustering center corresponding to the query image. Thirdly, QRC loss function is designed to enlarge the similarity between the query image and its dynamic cluster center to achieve query related clustering, so as to compact the intraclass variations. Consequently, in the proposed QRC method, each query has its own dynamic clustering center, which can well characterize intra-class variations in VIPR. Experimental results demonstrate that the proposed QRC method is superior to many state-of-the-art approaches, acquiring a 90. 77% rank-1 identification rate on the RegDB dataset. |
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