Artistic movement recognition by boosted fusion of color structure and topographic description

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

We address the problem of automatically recognizing artistic movement in digitized paintings. We make the following contributions: Firstly, we introduce a large digitized painting database that contains refined annotations of artistic movement. Secondly, we propose a new system for the automatic categorization that resorts to image descriptions by color structure and novel topographical features as well as to an adapted boosted ensemble of support vector machines. The system manages to isolate initially misclassified images and to correct such errors in further stages of the boosting process. The resulting performance of the system compares favorably with classical solutions in terms of accuracy and even manages to outperform modern deep learning frameworks.

TitelProceedings - 2017 IEEE Winter Conference on Applications of Computer Vision
Antal sider9
Publikationsdato11 maj 2017
ISBN (Elektronisk)978-1-5090-4822-9
StatusUdgivet - 11 maj 2017
Begivenhed17th IEEE Winter Conference on Applications of Computer Vision - Santa Rosa, USA
Varighed: 24 mar. 201731 mar. 2017
Konferencens nummer: 17


Konference17th IEEE Winter Conference on Applications of Computer Vision
BySanta Rosa

ID: 179556482