Affective space exploration for impressionism paintings

Cheng-Te Li, Man Kwan Shan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we explore the affective contents of Impressionism paintings. While past analysis of artworks concentrated on artistic concept annotation, like styles and periods, a more perceptual aspect is to investigate the emotions artists projected into. We propose affective space to fuse all affective factors from features. Since the combination of colors is more sensitive and intuitive to emotions, a meta-level feature, color harmony, is introduced to bridge the semantic gaps. By considering the correlation relationships among features and emotions, the affective space is explored through multiple-type latent semantic analysis. Experimental results show the effectiveness of harmonic feature and affective space via multi-label emotion annotation. Some potential applications are demonstrated based on affective space as well, including painting emotionalization and emotion-based slideshow system.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings
Pages387-396
Number of pages10
DOIs
Publication statusPublished - 2008 Dec 1
Event9th Pacific Rim Conference on Multimedia, PCM 2008 - Tainan, Taiwan
Duration: 2008 Dec 92008 Dec 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5353 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th Pacific Rim Conference on Multimedia, PCM 2008
CountryTaiwan
CityTainan
Period08-12-0908-12-13

Fingerprint

Painting
Semantics
Color
Electric fuses
Labels
Annotation
Latent Semantic Analysis
Intuitive
Harmonic
Emotion
Experimental Results

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Li, C-T., & Shan, M. K. (2008). Affective space exploration for impressionism paintings. In Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings (pp. 387-396). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5353 LNCS). https://doi.org/10.1007/978-3-540-89796-5_40
Li, Cheng-Te ; Shan, Man Kwan. / Affective space exploration for impressionism paintings. Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings. 2008. pp. 387-396 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Li, C-T & Shan, MK 2008, Affective space exploration for impressionism paintings. in Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5353 LNCS, pp. 387-396, 9th Pacific Rim Conference on Multimedia, PCM 2008, Tainan, Taiwan, 08-12-09. https://doi.org/10.1007/978-3-540-89796-5_40

Affective space exploration for impressionism paintings. / Li, Cheng-Te; Shan, Man Kwan.

Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings. 2008. p. 387-396 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5353 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Li C-T, Shan MK. Affective space exploration for impressionism paintings. In Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings. 2008. p. 387-396. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-89796-5_40