Name
Abstract | ||
|---|---|---|
Modeling the emotional response of human observers to specific imagery is an important aspect of affective computing; it both furthers our understanding of the affective qualities of visual stimuli and paves the way for numerous applications. The emotional effect of colors and their combinations have been extensively studied by artists, as color is one of the essential means of conveying the artist's intention and affecting viewers emotionally. This is especially true in abstract art. In this study, the authors show how concepts from art theory can be used to design a computational model that lets a computer predict whether an abstract painting will elicit positive or negative emotions in the observer. Furthermore, their model can be used to generate abstract paintings that elicit intended emotional responses in observers. This article is part of a special issue on quality modeling. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MMUL.2016.20 | IEEE MultiMedia |
Keywords | Field | DocType |
Image color analysis,Image recognition,Modeling,Art,Computational modeling,Feature extraction,Observers | Graphics,Abstract art,Computer science,Painting,Affective computing,Affect (psychology),Multimedia,Visual perception | Journal |
Volume | Issue | ISSN |
23 | 3 | 1070-986X |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreza Sartori | 1 | 41 | 3.22 |
| Dubravko Culibrk | 2 | 279 | 20.02 |
| Yan Yan | 3 | 691 | 31.13 |
| remo job | 4 | 1 | 2.06 |
| Nicu Sebe | 5 | 7013 | 403.03 |