Abstract
This study was designed to improve the limitations of traditional analysis of artworks by quantitatively analyzing artworks through biologically-motivated image processing techniques that reflect visual information processing mechanisms of human vision. As the first step to achieve this goal, this study addressed one of the important questions in art history, uncovering a mentor for ‘an artist who remains forever unknown’ Johannes Vermeer, by adopting three interdisciplinary research methods of cognitive science, art history, and engineering. We performed orientation, radial frequency, and color analyses with the artworks for comparing the artistic styles of Vermeer and other artists who have been presumed to be his mentor. The results from three analyses have led us to the conclusion that a person who had the strongest influence on Vermeer is Gerard Ter Borch. This conclusion was strongly confirmed by verifying the research methods with an additional comparison of artistic styles between Rembrandt and Carel Fabritius, whose master-pupil relationship has already been revealed. This study is believed to provide a new perspective on uncovering previously unknown mentor of Vermeer, and the research methods adopted here can be applied to other related research issues in art history, such as authenticity debates on masterpieces, by quantitatively archiving artists’ characteristic styles.
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Kim, M., Kim, J. (2013). Quantitative Analysis of Artists’ Characteristic Styles through Biologically-Motivated Image Processing Techniques: Uncovering a Mentor to Johannes Vermeer. In: Stephanidis, C. (eds) HCI International 2013 - Posters’ Extended Abstracts. HCI 2013. Communications in Computer and Information Science, vol 374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39476-8_53
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DOI: https://doi.org/10.1007/978-3-642-39476-8_53
Publisher Name: Springer, Berlin, Heidelberg
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