Mathematical foundations for quantifying shape, shading, and cast shadows in realist master drawings and paintings

David G. Stork

doi:10.1117/12.681141

25 August 2006 Mathematical foundations for quantifying shape, shading, and cast shadows in realist master drawings and paintings

David G. Stork

Author Affiliations +

Proceedings Volume 6315, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX; 63150K (2006) https://doi.org/10.1117/12.681141
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

The problem of inferring the two-dimensional location of an illuminant in an image, such as a digital photograph, has been studied as part of general scene analysis. One application area for analytical techniques and algorithms to this end is forensic image analysis, particularly in the detection of tampering and composites. For instance, if algorithms applied to two figures or two sections of an image reveal that these regions were captured under different lighting directions, it is highly likely that these regions were captured separately and later digitally integrated into the composite image, that is, the photograph was tampered. Recently some of these techniques have been applied to the study of realist master paintings and drawings in order to answer questions about the studio working methods of artists. We reveiw several sources of visual information about the location of the illuminant, stressing those most relevant to problems in the analysis of art, specifically paintings and drawings. We then present the foundations for a Bayesian method for integrating estimates from different sources, and then explore the application of such methods to the problem of inferring the location of the illuminant in realist paintings.

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David G. Stork "Mathematical foundations for quantifying shape, shading, and cast shadows in realist master drawings and paintings", Proc. SPIE 6315, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX, 63150K (25 August 2006); https://doi.org/10.1117/12.681141

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