Selective clustering for representative paintings selection

doi:10.1007/s11042-019-7271-7

	Selective clustering for representative paintings selection
	Deng, Yingying1,2,4 ; Tang, Fan1,2,4 ; Dong, Weiming1 ; Wu, Fuzhang 3; Deussen, Oliver ; Xu, Changsheng1
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
	2019-07-01
卷号	78 期号:14 页码:19305-19323
通讯作者	Dong, Weiming(weiming.dong@ia.ac.cn)
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.
关键词	Digital arts analysis Pattern mining Rejection mechanism Deep feature representation
DOI	10.1007/s11042-019-7271-7
关键词[WOS]	REJECT OPTION ; CLASSIFICATION ; STYLE
收录类别	SCI
语种	英语
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 ; 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
项目资助者	National Natural Science Foundation of China ; National Laboratory of Pattern Recognition
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000475703800017
出版者	SPRINGER
七大方向——子方向分类	图像视频处理与分析
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/23909
专题	多模态人工智能系统全国重点实验室_多媒体计算
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
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
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.