Digital Morphology of Ornaments – Novel Methods for the Analysis, Modelling and Research of Ornament Forms, linking Art History and Computer Vision, applied to Augsburg Rocaille Prints of the 18th Century

艺术史研究中很少有领域像罗卡耶装饰品研究这样具有基本的必要性。这些形式在1730年左右出现在法国，并成为世纪的主要形式，特别是在中欧。尽管有大量的物品--从鼻烟盒到巨大的灰泥作品--以及无穷无尽的各种形式，但令人遗憾的是，在日期、归属和科学评估方面仍然存在不确定性。这一缺陷的主要原因是术语上的困难-不规则的，贝壳状的形式逃避几何和图像描述。然而，传播和解释法国形式的装饰版画为全面分析提供了很好的机会。几千蚀刻起源于重要的出版中心奥格斯堡单独，显示艺术和工艺品和装饰形式，印刷之间的1730年和1775年。我们解决这一迫切需要通过采用跨学科的方法在艺术史和计算机科学之间的接口：形式的分析与技术，从计算机视觉领域，特别是结合图论和机器学习。对于一个可行的应用程序的rocaille形式，我们将开发新的方法，以使抽象的图像内容访问的算法技术的调查。基于现有的约2100幅数字化奥格斯堡版画，我们将开发一个工具链，根据相似性对作品进行分类，并识别相关的形式和作品。这一研究工具将使我们能够找到关于版画作为模型和图案的归属、年代和应用的基本问题的答案，从而打开当前艺术史理论的研究视角，特别是在文化转移和图像转向领域。我们的实现将基于将罗卡耶作品细分为一个由螺旋和附加的多态脊组成的框架的可能性。我们将提取几何，属性图描述和抽象的S-和C-形状的一组蜗壳，而我们将代表的千变万化的脊纹理与统计噪声参数化和子图。再加上适当的相似性措施，图形可视化范例，图形转换，我们将开发工具，提供新的可能性，研究装饰艺术史。

Few areas of art historical research are characterized by such elementary desiderata as studies on rocaille ornaments. These forms emerged in France around 1730 and became the predominant form of ornamentation of the 18th century, especially in Central Europe. Notwithstanding the large number of objects – from the snuffbox to the monumental stucco work – and a sheer inexhaustible variety of forms, a deplorable uncertainty in dating, attribution and scientific assessment still prevails. The main reason for this deficiency are terminological difficulties – the irregular, shell-like forms evade both a geometric and an iconographic description. Yet, ornamental prints in which the French forms were disseminated and interpreted offer great opportunities for a comprehensive analysis. Several thousand etchings originate from the important publishing center Augsburg alone, showing arts and crafts objects and decorative forms, printed between 1730 and 1775.We address this desideratum by employing an interdisciplinary approach at the interface between art history and computer science: the analysis of forms with techniques from the field of computer vision, especially in combination with graph theory and machine learning. For a feasible application to rocaille forms, we will develop new methods in order to make the abstract image contents accessible to an investigation with algorithmic techniques. Based on an already existing collection of about 2100 digitized Augsburg prints, we will develop a tool chain which categorizes the works according to similarities and enables the identification of related forms and works. This research tool will enable us to find answers to fundamental questions concerning the attribution, dating and application of prints as models and patterns, which in turn open up research perspectives in current art historical theory, especially in the areas of cultural transfer and the pictorial turn.Our realization will be based on the possibility of subdividing the rocaille compositions into a framework of volutes and the attached polymorphic ridges. We will extract geometric, attributed graphs describing and abstracting the set of S- and C-shapes of the volutes, while we will represent the protean ridges as textures with statistical noise parametrizations and sub-graphs. Together with suitable similarity measures, graph visualization paradigms, and graph transformations, we will develop tools that afford new possibilities for researching ornaments in art history.