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论通过边缘方向分布实现绘画的动态感

On the Dynamism of Paintings Through the Distribution of Edge Directions.

作者信息

Deliege Adrien, Dondero Maria Giulia, D'Armenio Enzo

机构信息

Department of Romance Languages and Literatures, Faculty of Philosophy and Letters, University of Liège, 4000 Liège, Belgium.

F.R.S.-FNRS, Rue d'Egmont 5, 1000 Bruxelles, Belgium.

出版信息

J Imaging. 2024 Nov 1;10(11):276. doi: 10.3390/jimaging10110276.

DOI:10.3390/jimaging10110276
PMID:39590740
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11595339/
Abstract

The digitization of artworks has recently offered new computational perspectives on the study of art history. While much of the focus has been on classifying styles or identifying objects, the analysis of more abstract concepts, such as the perception of motion or dynamism in still images, remains largely unexplored. Semioticians and artists have long explored the representation of dynamism in still images, but they often did so through theoretical frameworks or visual techniques, without a quantitative approach to measuring it. This paper proposes a method for computing and comparing the dynamism of paintings through edge detection. Our approach is based on the idea that the dynamism of a painting can be quantified by analyzing the edges in the image, whose distribution can be used to identify patterns and trends across artists and movements. We demonstrate the applicability of our method in three key areas: studying the temporal evolution of dynamism across different artistic styles, as well as within the works of a single artist (Wassily Kandinsky), visualizing and clustering a large database of abstract paintings through PixPlot, and retrieving similarly dynamic images. We show that the dynamism of a painting can be effectively quantified and visualized using edge detection techniques, providing new insights into the study of visual culture.

摘要

艺术品的数字化最近为艺术史研究提供了新的计算视角。虽然大部分研究重点都放在风格分类或物体识别上,但对于更抽象概念的分析,如静态图像中运动或动态感的感知,在很大程度上仍未得到充分探索。符号学家和艺术家长期以来一直在探索静态图像中动态感的表现,但他们往往是通过理论框架或视觉技巧来进行,而没有采用定量方法来衡量它。本文提出了一种通过边缘检测来计算和比较绘画动态感的方法。我们的方法基于这样一种理念,即一幅绘画的动态感可以通过分析图像中的边缘来量化,边缘的分布可用于识别不同艺术家和艺术运动中的模式和趋势。我们在三个关键领域展示了我们方法的适用性:研究不同艺术风格以及单个艺术家(瓦西里·康定斯基)作品中动态感的时间演变;通过PixPlot对大量抽象绘画数据库进行可视化和聚类;检索具有相似动态感的图像。我们表明,使用边缘检测技术可以有效地量化和可视化绘画的动态感,为视觉文化研究提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/3329dda7e1cf/jimaging-10-00276-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/abd835ca3b06/jimaging-10-00276-g0A1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/236917440fa5/jimaging-10-00276-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/01449704b3b9/jimaging-10-00276-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/024e6e747fb4/jimaging-10-00276-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/3329dda7e1cf/jimaging-10-00276-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/abd835ca3b06/jimaging-10-00276-g0A1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfd9/11595339/236917440fa5/jimaging-10-00276-g001.jpg
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