Knowledge Commons of Institute of Automation,CAS
Selective clustering for representative paintings selection | |
Deng, Yingying1,2,4; Tang, Fan1,2,4; Dong, Weiming1; Wu, Fuzhang3; 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 Laboratory of Pattern Recognition ; National Natural Science Foundation of China[61702488] ; National Natural Science Foundation of China[61672520] ; National Natural Science Foundation of China[61832016] ; 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 | |
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. |
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