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Proceedings Paper

Computer analysis of lighting style in fine art: steps towards inter-artist studies
Author(s): David G. Stork
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Paper Abstract

Stylometry in visual art-the mathematical description of artists' styles - has been based on a number of properties of works, such as color, brush stroke shape, visual texture, and measures of contours' curvatures. We introduce the concept of quantitative measures of lighting, such as statistical descriptions of spatial coherence, diuseness, and so forth, as properties of artistic style. Some artists of the high Renaissance, such as Leonardo, worked from nature and strove to render illumination "faithfully" photorealists, such as Richard Estes, worked from photographs and duplicated the "physics based" lighting accurately. As such, each had dierent motivations, methodologies, stagings, and "accuracies" in rendering lighting clues. Perceptual studies show that observers are poor judges of properties of lighting in photographs such as consistency (and thus by extension in paintings as well); computer methods such as rigorous cast-shadow analysis, occluding-contour analysis and spherical harmonic based estimation of light fields can be quite accurate. For this reasons, computer lighting analysis can provide a new tools for art historical studies. We review lighting analysis in paintings such as Vermeer's Girl with a pearl earring, de la Tour's Christ in the carpenter's studio, Caravaggio's Magdalen with the smoking flame and Calling of St. Matthew) and extend our corpus to works where lighting coherence is of interest to art historians, such as Caravaggio's Adoration of the Shepherds or Nativity (1609) in the Capuchin church of Santa Maria degli Angeli. Our measure of lighting coherence may help reveal the working methods of some artists and in diachronic studies of individual artists. We speculate on artists and art historical questions that may ultimately profit from future renements to these new computational tools.

Paper Details

Date Published: 10 March 2011
PDF: 11 pages
Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 786903 (10 March 2011); doi: 10.1117/12.873190
Show Author Affiliations
David G. Stork, Ricoh Innovations, Inc. (United States)

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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