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Fuzzy Multilayer Clustering and Fuzzy Label Regularization for Unsupervised Person Reidentification

文献类型：期刊论文

作者Zhang, Zhong3; Huang, Meiyan3; Liu, Shuang3; Xiao, Baihua2; Durrani, Tariq S.1
刊名IEEE TRANSACTIONS ON FUZZY SYSTEMS
出版日期2020-07-01
卷号28期号:7页码:1356-1368
ISSN号1063-6706
关键词Databases Multilayer perceptrons Nonhomogeneous media Training Feature extraction Clustering algorithms Cameras Fuzzy multilayer clustering (FMC) fuzzy label regularization (FLR) unsupervised person reidentification
DOI10.1109/TFUZZ.2019.2914626
通讯作者Zhang, Zhong(zhong.zhang8848@gmail.com)
英文摘要Unsupervised person reidentification has received more attention due to its wide real-world applications. In this paper, we propose a novel method named fuzzy multilayer clustering (FMC) for unsupervised person reidentification. The proposed FMC learns a new feature space using a multilayer perceptron for clustering in order to overcome the influence of complex pedestrian images. Meanwhile, the proposed FMC generates fuzzy labels for unlabeled pedestrian images, which simultaneously considers the membership degree and the similarity between the sample and each cluster. We further propose the fuzzy label regularization (FLR) to train the convolutional neural network (CNN) using pedestrian images with fuzzy labels in a supervised manner. The proposed FLR could regularize the CNN training process and reduce the risk of overfitting. The effectiveness of our method is validated on three large-scale person reidentification databases, i.e., Market-1501, DukeMTMC-reID, and CUHK03.
WOS关键词RECOGNITION
资助项目National Natural Science Foundation of China[61501327] ; National Natural Science Foundation of China[61711530240] ; Natural Science Foundation of Tianjin[17JCZDJC30600] ; Fund of Tianjin Normal University[135202RC1703] ; Open Projects Program of National Laboratory of Pattern Recognition[201700001] ; Open Projects Program of National Laboratory of Pattern Recognition[201800002] ; China Scholarship Council[201708120039] ; China Scholarship Council[201708120040] ; Tianjin Higher Education Creative Team Funds Program ; NSFC-Royal Society Grant
WOS研究方向Computer Science ; Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000545205300015
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Tianjin ; Fund of Tianjin Normal University ; Open Projects Program of National Laboratory of Pattern Recognition ; China Scholarship Council ; Tianjin Higher Education Creative Team Funds Program ; NSFC-Royal Society Grant
源URL[http://ir.ia.ac.cn/handle/173211/40096]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队
通讯作者Zhang, Zhong
作者单位1.Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XQ, Lanark, Scotland
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Tianjin Normal Univ, Tianjin Key Lab Wireless Mobile Commun & Power Tr, Tianjin 300387, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Zhong,Huang, Meiyan,Liu, Shuang,et al. Fuzzy Multilayer Clustering and Fuzzy Label Regularization for Unsupervised Person Reidentification[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS,2020,28(7):1356-1368.
APA Zhang, Zhong,Huang, Meiyan,Liu, Shuang,Xiao, Baihua,&Durrani, Tariq S..(2020).Fuzzy Multilayer Clustering and Fuzzy Label Regularization for Unsupervised Person Reidentification.IEEE TRANSACTIONS ON FUZZY SYSTEMS,28(7),1356-1368.
MLA Zhang, Zhong,et al."Fuzzy Multilayer Clustering and Fuzzy Label Regularization for Unsupervised Person Reidentification".IEEE TRANSACTIONS ON FUZZY SYSTEMS 28.7(2020):1356-1368.

入库方式： OAI收割

来源：自动化研究所

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