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

Corneliu Florea; Cosmin Toca; Fabian Cristian Gieseke

doi:10.1109/WACV.2017.69

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

Corneliu Florea, Cosmin Toca, Fabian Cristian Gieseke

Datalogisk Institut

14 Citationer (Scopus)

Abstract

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.

Originalsprog	Engelsk
Titel	Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision
Antal sider	9
Forlag	IEEE
Publikationsdato	11 maj 2017
Sider	569-577
ISBN (Elektronisk)	978-1-5090-4822-9
DOI	https://doi.org/10.1109/WACV.2017.69
Status	Udgivet - 11 maj 2017
Begivenhed	17th IEEE Winter Conference on Applications of Computer Vision - Santa Rosa, USA Varighed: 24 mar. 2017 → 31 mar. 2017 Konferencens nummer: 17

Konference

Konference	17th IEEE Winter Conference on Applications of Computer Vision
Nummer	17
Land/Område	USA
By	Santa Rosa
Periode	24/03/2017 → 31/03/2017

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10.1109/WACV.2017.69

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Citationsformater

Florea, C, Toca, C & Gieseke, FC 2017, Artistic movement recognition by boosted fusion of color structure and topographic description. i Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision. IEEE, s. 569-577, 17th IEEE Winter Conference on Applications of Computer Vision, Santa Rosa, California, USA, 24/03/2017. https://doi.org/10.1109/WACV.2017.69

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abstract = "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.",

author = "Corneliu Florea and Cosmin Toca and Gieseke, {Fabian Cristian}",

year = "2017",

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language = "English",

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AB - 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.

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

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