Visual Computing

University of Konstanz
Multimedia Tools and Applications

Selective clustering for representative paintings selection

Y. Deng, F. Tang, W. Dong, F. Wu, O. Deussen, C. Xu
Teaser of Selective clustering for representative paintings selection

Our representative painting selection result for Claude Monet

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 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.

BibTeX

@article{Deng2019Selectiveclusteringrepresentative,
  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 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.},
  author     = {Y. Deng and F. Tang and W. Dong and F. Wu and O. Deussen and C. Xu},
  day        = {09},
  doi        = {10.1007/s11042-019-7271-7},
  issn       = {1573-7721},
  journal    = {Multimedia Tools and Applications},
  month      = {Feb},
  title      = {Selective clustering for representative paintings selection},
  url        = {https://doi.org/10.1007/s11042-019-7271-7},
  year       = {2019},
}