文章基本信息

标题：Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder
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作者：James M. Hughes ; Daniel J. Graham ; Daniel N. Rockmore 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2010
卷号：107
期号：4
页码：1279-1283
DOI：10.1073/pnas.0910530107
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Recently, statistical techniques have been used to assist art historians in the analysis of works of art. We present a novel technique for the quantification of artistic style that utilizes a sparse coding model. Originally developed in vision research, sparse coding models can be trained to represent any image space by maximizing the kurtosis of a representation of an arbitrarily selected image from that space. We apply such an analysis to successfully distinguish a set of authentic drawings by Pieter Bruegel the Elder from another set of well-known Bruegel imitations. We show that our approach, which involves a direct comparison based on a single relevant statistic, offers a natural and potentially more germane alternative to wavelet-based classification techniques that rely on more complicated statistical frameworks. Specifically, we show that our model provides a method capable of discriminating between authentic and imitation Bruegel drawings that numerically outperforms well-known existing approaches. Finally, we discuss the applications and constraints of our technique.
关键词：art analysis ; art authentication ; image classification ; machine learning ; stylometry