Computer vision, a new ally for the analysis of artistic images
Keywords:
artificial visión, Bag-of-visterms, SIFT descriptors, images catalogation, automatic analysis of images
Agencies:
Ayudas para la realización de proyectos de investigación pre competitivos en Ciencias Sociales y Humanas (APPCSHUM), Vicerrectorado de Política Docente y Científica de la Universitat de Barcelona, 2011 – 2012
Abstract
This paper analyzes the automatic classification of scenes that are the basis of the ideation and the designing of the sculptural production of the sculptor Miquel Planas. The main purpose is to evaluate the performance of the Bag-of-Features methods, in the challenging task of categorizing scenes when scenes differ in semantics rather than the objects they contain. We have employed a kernel-based recognition method that works by computing rough geometric correspondence on a global scale using the pyramid matching scheme introduced by Lazebnik, Schmid and Ponce in 2006. Results are promising, on average the score is about 70%. Experiments suggest that the automatic categorization of images based on computer vision methods can provide objective principles in cataloging images.Format
Crossmark
Published
2016-04-08
How to Cite
Rosado-Rodrigo, P., Figueras-Ferrer, E., Planas-Rosselló, M., & Reverter-Comes, F. (2016). Computer vision, a new ally for the analysis of artistic images. Arte, Individuo Y Sociedad, 28(2), 339-354. https://doi.org/10.5209/rev_ARIS.2016.v28.n2.48802
Issue
Section
Articles
License
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