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Proceedings Paper

Time and order estimation of paintings based on visual features and expert priors
Author(s): Ricardo S. Cabral; João P. Costeira; Fernando de La Torre; Alexandre Bernardino; Gustavo Carneiro
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Paper Abstract

Time and order are considered crucial information in the art domain, and subject of many research efforts by historians. In this paper, we present a framework for estimating the ordering and date information of paintings and drawings. We formulate this problem as the embedding into a one dimension manifold, which aims to place paintings far or close to each other according to a measure of similarity. Our formulation can be seen as a manifold learning algorithm, albeit properly adapted to deal with existing questions in the art community. To solve this problem, we propose an approach based in Laplacian Eigenmaps and a convex optimization formulation. Both methods are able to incorporate art expertise as priors to the estimation, in the form of constraints. Types of information include exact or approximate dating and partial orderings. We explore the use of soft penalty terms to allow for constraint violation to account for the fact that prior knowledge may contain small errors. Our problem is tested within the scope of the PrintART project, which aims to assist art historians in tracing Portuguese Tile art "Azulejos" back to the engravings that inspired them. Furthermore, we describe other possible applications where time information (and hence, this method) could be of use in art history, fake detection or curatorial treatment.

Paper Details

Date Published: 8 March 2011
PDF: 10 pages
Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 78690G (8 March 2011); doi: 10.1117/12.872256
Show Author Affiliations
Ricardo S. Cabral, Univ. Técnica de Lisboa (Portugal)
Carnegie Mellon Univ. (United States)
João P. Costeira, Univ. Técnica de Lisboa (Portugal)
Fernando de La Torre, Carnegie Mellon Univ. (United States)
Alexandre Bernardino, Univ. Técnica de Lisboa (Portugal)
Gustavo Carneiro, Univ. Técnica de Lisboa (Portugal)

Published in SPIE Proceedings Vol. 7869:
Computer Vision and Image Analysis of Art II
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)

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