CHS: Medium: Collaborative Research: Integrated Simulation of Cloth Mechanics and Appearance for Predictive Virtual Prototyping

CHS：媒介：协作研究：用于预测虚拟原型制作的布料力学和外观集成仿真

• 批准号: 1513967
• 负责人: Steve Marschner
• 金额: $ 95万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513967&HistoricalAwards=false
• 关键词: CHS; Medium; Collaborative; Research; Integrated

Simulated virtual prototypes have removed much trial-and-error from the design process in many fields. But to be useful as a virtual prototype, a simulation must reliably predict the relevant characteristics of the thing being designed: strength for a bridge; lift for an aircraft, or appearance for a fabric. Previous advances in rendering have led to a current explosion in the use of rendered images to prototype the appearance of objects, and even to represent them to customers, but only where the materials involved can be represented well. Textiles are currently difficult to represent, due to their intricate construction and subtle reflectance, and because their appearance is inextricably linked to their shape and motion. Although fairly suitable for movies, the state of the art in simulating cloth appearance and deformation is not predictive of real appearance and therefore not usable in a design process, in which realistic but inaccurate results are useless. This project, which represents a collaborative effort between computer scientists at Cornell University and textile designers at the Rhode Island School of Design, aims to create the predictive simulation tools needed to enable virtual prototyping to revolutionize the textile and garment industries in the same way it has already revolutionized so many fields of manufacturing. New models and algorithms created by the Cornell team will be integrated into the Loomit tool for fabric design, which will then be used by the RISD team to produce new textiles that will in turn be shipped back to Cornell where changes in the RISD design process resulting from Loomit's enhanced capabilities will be studied. At RISD this involvement will engage many student artists and designers, helping them develop the skills to work with increasingly technological media in their future careers, while at Cornell the project will afford computer science students experience understanding and solving problems faced by artists and designers.Textiles remain a challenge for appearance simulation because of many unsolved fundamental problems. The state-of-the-art models for realistic cloth rendering and simulation were developed for entertainment applications and do not accurately predict the behavior of real textiles. In this project, the PI team will compare appearance and deformation models to measurements of textiles from CT, imaging, and other modalities, then improve them as needed so that they are capable of fitting real materials. Current methods cannot capture the properties of an existing fabric well enough to predict its appearance under close visual inspection. The PI team will develop new methods for jointly capturing the appearance and mechanical properties of textiles, combining measurement and model tuning to produce predictive working models of textiles and the garments and furnishings made from them. Detailed cloth simulations and renderings are currently impractical for moderately complex objects, such as complete garments. Scalability fundamentally requires multi-scale models that simulate details only when they are actually needed. The PI team will create multi-scale models that enable interactive, predictive visualization during the design process. Since the targeted applications all require accurate prediction, a major focus of the research is on validation, testing both the accuracy of the individual technical pieces and the ultimate usefulness of the new techniques in actual use.

在许多领域，模拟虚拟样机已经从设计过程中消除了大量的反复试验。但要想成为有用的虚拟原型，模拟必须可靠地预测正在设计的东西的相关特征：桥梁的强度、飞机的升力或织物的外观。以前在渲染方面的进步导致了当前使用渲染图像来制作对象外观的原型，甚至向客户表示它们，但只有在所涉及的材质可以很好地表示的情况下才会出现爆炸性的使用。纺织品目前很难代表，因为它们复杂的结构和微妙的反射，而且它们的外观与它们的形状和运动密不可分。尽管相当适合于电影，但模拟布料外观和变形的最新技术并不能预测真实的外观，因此在设计过程中不可用，在设计过程中，逼真但不准确的结果是无用的。该项目代表着康奈尔大学的计算机科学家和罗德岛设计学院的纺织品设计师的合作努力，旨在创造所需的预测性模拟工具，使虚拟原型技术能够像它已经给众多制造领域带来革命性的那样，给纺织和服装行业带来革命性的变化。康奈尔大学团队创建的新模型和算法将被集成到Loomit面料设计工具中，然后RISD团队将使用这些工具来生产新的纺织品，这些新面料将被运回康奈尔大学，在那里将研究Loomit增强能力导致的RISD设计过程中的变化。在RISD，这种参与将吸引许多学生艺术家和设计师，帮助他们在未来的职业生涯中发展与日益技术的媒体合作的技能，而在康奈尔，该项目将为计算机科学专业的学生提供了解和解决艺术家和设计师面临的问题的机会。由于许多尚未解决的基本问题，纺织品仍然是外观模拟的一个挑战。最先进的真实感布料渲染和模拟模型是为娱乐应用开发的，无法准确预测真实纺织品的行为。在这个项目中，PI团队将比较外观和变形模型与来自CT、成像和其他模式的纺织品测量结果，然后根据需要进行改进，使其能够适应真实材料。目前的方法不能很好地捕捉现有织物的属性，以便在近距离目测下预测其外观。PI团队将开发联合捕获纺织品外观和机械性能的新方法，将测量和模型调整相结合，以产生纺织品及其服装和家具的预测工作模型。详细的Cloth模拟和渲染目前不适用于中等复杂的对象，例如完整的服装。可伸缩性从根本上要求多尺度模型仅在实际需要时才模拟细节。PI团队将创建多比例模型，以在设计过程中实现交互式、预测性可视化。由于目标应用都需要准确的预测，因此研究的主要重点是验证，测试单个技术部件的准确性和新技术在实际使用中的最终用处。