CHS: Small: Collaborative Research: 3D Printing for High Fidelity Image Reproduction Capturing Texture, Spectral Color, Gloss, and Translucency
CHS: Small: Collaborative Research: 3D Printing for High Fidelity Image Reproduction Capturing Texture, Spectral Color, Gloss, and Translucency
批准号:
1815070
负责人:
Szymon Rusinkiewicz
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-08-31
中文摘要
CHS:小型:合作研究:用于高保真图像再现的3D打印捕捉纹理,光谱颜色,光泽和半透明3D打印可以利用多种材料的精细交错来制造其他技术无法制造的物体。特别是,由多材料增材制造实现的一个新的研究领域是制造具有理想外观性能的物体。该项目将开发超高保真再现纹理、光谱颜色、光泽和半透明的技术。虽然消费级打印机通常使用4种油墨颜色,但我们的系统将使用10种不同的油墨,以准确地再现整个光谱的颜色,包括在可见性边缘的区域。使用这些3D打印机不仅可以再现色彩,还可以再现光泽、半透明和精细的细节,如笔触。我们对这项工作的测试平台是绘制精美的艺术图像。这一领域提供了技术挑战,将推动高保真复制技术的发展,并立即使文化遗产保护工作受益。精美的艺术品在长时间展出时,本质上容易受到光线和空气的退化或损坏。这些文化瑰宝的超高质量复制品可以在许多应用中取代原件,包括修复实践、音乐学院研究、博物馆教育和家庭娱乐。与波士顿和普林斯顿当地博物馆的合作,将有助于与策展人和公众建立强有力的联系。项目成果将产生额外的广泛影响,通过3D打印实现精确的外观再现,支持快速原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,有一个问题是如何使用先进的摄像系统来捕捉原画的属性。这包括测量画上每个点折射的全光谱,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细微凸起。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,并将测量的油墨特性结合到计算机模拟中,以准确预测打印输出的外观。该项目的最后组成部分是执行计算机优化,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达到最大的复制质量。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知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
CHS: Small: Collaborative Research: 3D Printing for High Fidelity Image Reproduction Capturing Texture, Spectral Color, Gloss, and Translucency3D printing can exploit fine-scale interleaving of multiple materials to enable fabrication of objects that have not been possible to make with other technologies. In particular, a novel research area enabled by multi-material additive manufacturing is the fabrication of objects with desired appearance properties. This project will develop technology for ultra-high fidelity reproduction of texture, spectral color, gloss, and translucency. While consumer-grade printers typically use 4 ink colors, our system will employ 10 different inks in order to accurately reproduce color across the spectrum, including regions that are at the edge of visibility. The use of these 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. Our testbed for this work is painted fine art images. This domain provides technical challenges that will push the state of the art for high-fidelity reproduction in general, as well as immediately benefiting cultural heritage preservation efforts. Fine art objects are inherently subject to degradation or damage from light and air when on display for long periods of time. Ultra-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. 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 refracted 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.
期刊论文(4)
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DOI:
10.1145/3272127.3275057
发表时间:
2018-12
期刊:
ACM Transactions on Graphics (TOG)
影响因子:
--
作者:
[Liang Shi;Vahid Babaei;Changil Kim;Michael Foshey;Yuanming Hu;Pitchaya Sitthi-amorn;S. Rusinkiewicz;W. Matusik]
通讯作者:
Liang Shi;Vahid Babaei;Changil Kim;Michael Foshey;Yuanming Hu;Pitchaya Sitthi-amorn;S. Rusinkiewicz;W. Matusik
DOI:
10.1145/3528223.3530144
发表时间:
2022-07-01
期刊:
ACM TRANSACTIONS ON GRAPHICS
影响因子:
6.2
作者:
[Piovarci, Michal, Foshey, Michael, Bickel, Bernd]
通讯作者:
Bickel, Bernd
DOI:
10.1145/3414685.3417850
发表时间:
2020-11
期刊:
ACM Transactions on Graphics (TOG)
影响因子:
--
作者:
[Michal Piovarči;Michael Foshey;Vahid Babaei;S. Rusinkiewicz;W. Matusik;P. Didyk]
通讯作者:
Michal Piovarči;Michael Foshey;Vahid Babaei;S. Rusinkiewicz;W. Matusik;P. Didyk
DOI:
--
发表时间:
2021-06
期刊:
ArXiv
影响因子:
--
作者:
[Xingyuan Sun;Tianju Xue;S. Rusinkiewicz;Ryan P. Adams]
通讯作者:
Xingyuan Sun;Tianju Xue;S. Rusinkiewicz;Ryan P. Adams
CHS: Small: Collaborative Research: Detailed Shape and Reflectance Capture with Light Field Cameras
-
批准号:1617236
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2016
-
负责人:Szymon Rusinkiewicz
-
依托单位:
RI: Small: Micro-GPS: Localization using Visual Landmarks in Commonplace Texture
-
批准号:1421435
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2014
-
负责人:Szymon Rusinkiewicz
-
依托单位:
CDI-Type I: Automated Documentation and Illustration of Material Culture through the Collaborative Algorithmic Rendering Engine (CARE)
-
批准号:1027962
-
项目类别:Standard Grant
-
资助金额:$55.5万
-
财政年份:2010
-
负责人:Szymon Rusinkiewicz
-
依托单位:
HCC: Large: Collaborative Research: Beyond Flat Images: Acquiring, Processing, and Fabricating Visually Rich Material Appearance
-
批准号:1012147
-
项目类别:Standard Grant
-
资助金额:$49.81万
-
财政年份:2010
-
负责人:Szymon Rusinkiewicz
-
依托单位:
Images with Normals: Acquisition, Analysis, and Depiction
-
批准号:0702580
-
项目类别:Continuing Grant
-
资助金额:$30.0万
-
财政年份:2007
-
负责人:Szymon Rusinkiewicz
-
依托单位:
CAREER: Practical 3D Model Acquisition
-
批准号:0347427
-
项目类别:Continuing Grant
-
资助金额:$44.83万
-
财政年份:2004
-
负责人:Szymon Rusinkiewicz
-
依托单位:
国内基金
海外基金
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