CASIA OpenIR  > 多媒体计算与图形学团队
Selective clustering for representative paintings selection
Yingying Deng1,2; Fan Tang1,2; Weiming Dong1; FuzhangWu3; Oliver Deussen4; Changsheng Xu1
Source PublicationMultimedia Tools and Applications
2019-02
Issue1Pages:1-19
Abstract

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 styleoriented 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.

KeywordDigital Arts Analysis Pattern Mining Rejection Mechanism Deep Feature Representation
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23909
Collection多媒体计算与图形学团队
Corresponding AuthorWeiming Dong
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.Institute of Software, Chinese Academy of Sciences
4.University of Konstanz
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yingying Deng,Fan Tang,Weiming Dong,et al. Selective clustering for representative paintings selection[J]. Multimedia Tools and Applications,2019(1):1-19.
APA Yingying Deng,Fan Tang,Weiming Dong,FuzhangWu,Oliver Deussen,&Changsheng Xu.(2019).Selective clustering for representative paintings selection.Multimedia Tools and Applications(1),1-19.
MLA Yingying Deng,et al."Selective clustering for representative paintings selection".Multimedia Tools and Applications .1(2019):1-19.
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