Name
Abstract | ||
|---|---|---|
An approach for style painting categorization based on their Qualitative Colour Descriptors (QCD) and their similarity (SimQCD) is presented in this paper. For learning the colour features of paintings from Baroque, Impressionism and Post-Impressionism styles, two classifiers are built based on k-Nearest Neighbour (k-NN) and support vector machine (SVM) methods. The results showed accuracies of categorization higher than 75%. Colour logics in art styles are identified from the literature in order to improve and explain the categorization obtained. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3233/978-1-61499-578-4-227 | Frontiers in Artificial Intelligence and Applications |
Keywords | Field | DocType |
qualitative colour,colour naming,colour similarity,SVM,art,logics | Support vector machine,Artificial intelligence,Mathematics,Machine learning | Conference |
Volume | ISSN | Citations |
277 | 0922-6389 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zoe Falomir | 1 | 119 | 24.98 |
| Lledó Museros Cabedo | 2 | 54 | 10.73 |
| Ismael Sanz | 3 | 102 | 19.17 |
| Luis Gonzalez-Abril | 4 | 102 | 20.14 |