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Selective clustering for representative paintings selection

文献类型：期刊论文

作者Deng, Yingying1,2,4; Tang, Fan1,2,4; Dong, Weiming1; Wu, Fuzhang3; Deussen, Oliver; Xu, Changsheng1
刊名MULTIMEDIA TOOLS AND APPLICATIONS
出版日期2019-07-01
卷号78期号:14页码:19305-19323
关键词Digital arts analysis Pattern mining Rejection mechanism Deep feature representation
ISSN号1380-7501
DOI10.1007/s11042-019-7271-7
通讯作者Dong, Weiming(weiming.dong@ia.ac.cn)
英文摘要Selective classification (or rejection based classification) has been proved useful in many applications. In this paper we describe a selective clustering framework with reject option to carry out large-scale digital arts analysis. With the help of deep learning techniques, we extract content-style features from a pre-trained convolutional network for the paintings. By proposing a rejection mechanism under Bayesian framework, we focus on selecting style-oriented representative paintings of an artist, which is an interesting and challenging cultural heritage application. Two kinds of samples are rejected during the rejection based robust continuous clustering process. Representative paintings are selected during the selective clustering phase. Visual qualitative analysis on small painting set and large scale quantitative experiments on a subset of Wikiart show that the proposed rejection based selective clustering approach outperforms the standard clustering methods.
WOS关键词REJECT OPTION ; CLASSIFICATION ; STYLE
资助项目National Natural Science Foundation of China[61832016] ; National Natural Science Foundation of China[61672520] ; National Natural Science Foundation of China[61702488] ; National Laboratory of Pattern Recognition
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000475703800017
出版者SPRINGER
资助机构National Natural Science Foundation of China ; National Laboratory of Pattern Recognition
源URL[http://ir.ia.ac.cn/handle/173211/23909]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Dong, Weiming
作者单位1.Chinese Acad Sci, Inst Automat, NLPR LIAMA, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Software, Beijing, Peoples R China
4.Univ Konstanz, Constance, Germany
推荐引用方式
GB/T 7714		 Deng, Yingying,Tang, Fan,Dong, Weiming,et al. Selective clustering for representative paintings selection[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2019,78(14):19305-19323.
APA Deng, Yingying,Tang, Fan,Dong, Weiming,Wu, Fuzhang,Deussen, Oliver,&Xu, Changsheng.(2019).Selective clustering for representative paintings selection.MULTIMEDIA TOOLS AND APPLICATIONS,78(14),19305-19323.
MLA Deng, Yingying,et al."Selective clustering for representative paintings selection".MULTIMEDIA TOOLS AND APPLICATIONS 78.14(2019):19305-19323.

入库方式： OAI收割

来源：自动化研究所

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