Name
Abstract | ||
|---|---|---|
The artistic style of paintings constitutes an important information about the painter's technique. It can provide a rich description of this technique using image processing tools, and particularly using image features. In this paper, we investigate automatic face detection in the Tenebrism style, a particular painting style that is characterized by the use of extreme contrast between the light and dark. We show that convolutional neural network along with an adapted learning base makes it possible to detect faces with a maximum accuracy in this style. This result is particularly interesting since it can be the basis of an illuminant study in the Tenebrism style. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-01449-0_28 | ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2018 |
Keywords | Field | DocType |
Face detection,Realist art,Illumination comprehension,Deep learning | Computer vision,Pattern recognition,Feature (computer vision),Convolutional neural network,Computer science,Painting,Image processing,Inpainting,Standard illuminant,Artificial intelligence,Deep learning,Face detection | Conference |
Volume | ISSN | Citations |
11182 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olfa Mzoughi | 1 | 0 | 0.68 |
| André Bigand | 2 | 43 | 6.30 |
| Christophe Renaud | 3 | 21 | 7.00 |