Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder
Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder
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DOI：
10.1073/pnas.0910530107
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发表时间：
2010-01-26
影响因子：
11.1
通讯作者：
Rockmore, Daniel N.
中科院分区：
文献类型：
--
作者：
Hughes, James M.;Graham, Daniel J.;Rockmore, Daniel N.
最近，统计技术已被用来协助艺术史学家分析艺术作品。我们提出了一种利用稀疏编码模型来量化艺术风格的新技术。稀疏编码模型最初是在视觉研究中开发的，可以通过最大化从该空间中任意选择的图像的表示的峰度来训练稀疏编码模型来表示任何图像空间。我们应用这样的分析，成功地区分了老彼得·勃鲁盖尔的一组真实绘画与另一组著名的勃鲁盖尔仿制品。我们表明，我们的方法涉及基于单个相关统计数据的直接比较，为依赖于更复杂的统计框架的基于小波的分类技术提供了一种自然且可能更切合实际的替代方案。具体来说，我们表明我们的模型提供了一种能够区分真实和仿制勃鲁盖尔绘画的方法，该方法在数值上优于众所周知的现有方法。最后，我们讨论了我们技术的应用和限制。
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.