CHS: Small: Collaborative Research: 3D Printing for High Fidelity Image Reproduction Capturing Texture, Spectral Color, Gloss, and Translucency

绘画等艺术品是我们社会和文化遗产的重要组成部分，但它们本身就容易退化或损坏。保护这些珍贵的作品需要付出巨大的代价，但如果后代要有机会欣赏它们并从中学习，那么保护它们是至关重要的。幸运的是，这些文化瑰宝的高质量复制品可以在许多应用中取代原件，包括修复实践、音乐研究、博物馆教育和家庭娱乐。该项目将探索如何利用新一代高质量3D打印机，通过不仅使用少量墨水(就像消费级打印机一样)，而且使用多达10种现有墨水来复制颜色，以便在各种照明条件下无法从原始图像和人眼中辨别出来，从而生产出具有前所未有质量的美术绘画复制品。此外，这些现代多材质3D打印机的使用不仅可以再现颜色，还可以再现光泽、半透明和笔触等尺寸的细节。通过创建第一个用于逼真复制艺术(重点是绘画)的完整管道，该项目将为总体上如何使用计算过程和3D打印机完成艺术复制奠定基础。这将使复制和保护文化遗产的技术成为可能，使广大民众能够以与原作难以区分的形式欣赏最喜欢的绘画。与波士顿和普林斯顿当地博物馆的合作将使策展人和普通公众能够进行强有力的接触。项目成果将产生更广泛的影响，通过3D打印实现准确的外观再现，以支持快速成型和最终用户产品制造的广泛应用。为了实现这些目标，该项目将研究几种关键方法和技术。首先，存在如何使用先进的摄像系统来捕捉原始画作的属性的问题。这包括测量油画上每个点反射的全光谱光线，以及表面的光泽或不透明程度。此外，它还涉及使用高分辨率3D扫描仪来测量刷子或其他工具在表面留下的凸起。该项目的第二个组成部分是表征多材料3D打印机的全部功能，并将测量的墨水特性纳入计算机模拟，以准确预测打印结果的外观。该项目的组成部分是进行计算机优化，以确定应该使用的印刷材料的确切类型、数量和浓度，以及如何调整印刷过程以实现最大的复制质量。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Fine art objects such as paintings form a key part of our social and cultural heritage, but are inherently subject to degradation or damage. Conservation of these precious works incurs a huge cost, yet is vital if future generations are to have an opportunity to enjoy them and learn from them. Fortunately, high quality facsimiles of these cultural treasures can be exploited in place of the originals in many applications, including restoration practice, conservatory studies, education in museums, and enjoyment at home. This project will explore how to exploit an emerging generation of high-quality 3D printers to produce reproductions of fine art paintings that are of unprecedented quality by using not just a small number of inks (as with consumer-grade printers) but as many as 10 different inks to reproduce colors such that they are indistinguishable from the original to the human eye under various lighting conditions. Moreover, the use of these modern multi-material 3D printers will enable not just the reproduction of color but also the recreation of gloss, translucency, and fine-scale detail such as brush strokes. By creating the first complete pipeline for realistic reproduction of fine art (with a focus on paintings), this project will lay the foundations for how fine art reproduction, in general, should be done using computational processes and 3D printers. This will lead to enabling technologies for reproduction and preservation of cultural heritage, allowing a wide population to enjoy favorite paintings in a form that is indistinguishable from the originals. Collaboration with local museums in Boston and Princeton will enable strong outreach with curators and the general public. Project outcomes will have additional broad impact by enabling accurate appearance reproduction with 3D printing in support of a wide range of applications in rapid prototyping and the manufacture of end-user products.To achieve these goals, the project will investigate several key methods and technologies. First, there is the question of how to use advanced camera systems to capture the properties of the original paintings. This involves measuring the full spectrum of light reflected by each point on the painting, as well as how shiny or opaque the surface is. Moreover, it involves the use of high-resolution 3D scanners to measure the fine bumps on the surface left by brushes or other tools. A second component of the project is to characterize the full capabilities of multi-material 3D printers, and to incorporate the measured ink properties into computer simulations that can predict exactly how the print-outs will look. The final components of the project are to perform computer optimization to determine the exact type, number, and concentration of printing materials that should be used, and how the printing process should be tweaked to achieve maximum reproduction quality.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.