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

基本信息

  • 批准号:
    1513954
  • 负责人:
  • 金额:
    $ 24.42万
  • 依托单位:
  • 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 2019-08-31
  • 项目状态:
    已结题

项目摘要

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.
仿真虚拟样机在许多领域的设计过程中消除了大量的试错。 但是,作为一个有用的虚拟原型,仿真必须可靠地预测正在设计的东西的相关特性:桥梁的强度;飞机的升力,或织物的外观。 渲染技术的进步已经导致了当前使用渲染图像来原型化对象外观的爆炸式增长,甚至将它们呈现给客户,但只有在所涉及的材料可以很好地表示的情况下。 纺织品目前很难表示,由于其复杂的结构和微妙的反射,因为他们的外观是密不可分的联系到他们的形状和运动。 虽然相当适合于电影,但模拟布料外观和变形的现有技术不能预测真实的外观,因此不能用于设计过程,其中逼真但不准确的结果是无用的。 该项目代表了康奈尔大学计算机科学家和罗得岛设计学院纺织品设计师之间的合作努力,旨在创建所需的预测仿真工具,使虚拟原型设计能够以革命性的方式彻底改变纺织和服装行业,就像它已经彻底改变了许多制造领域一样。 康奈尔大学团队创建的新模型和算法将被集成到用于织物设计的Loomit工具中,然后RISD团队将使用该工具生产新的纺织品,然后将这些纺织品运回康奈尔大学,在那里RISD设计过程中因Loomit的增强而产生的变化将被研究。 在RISD,这个项目将吸引许多学生艺术家和设计师,帮助他们发展在未来职业生涯中与越来越多的技术媒体合作的技能,而在康奈尔大学,这个项目将让计算机科学专业的学生体验理解和解决艺术家和设计师面临的问题。纺织品仍然是外观模拟的挑战,因为有许多未解决的基本问题。 用于真实布料渲染和模拟的最先进的模型是为了娱乐应用而开发的,并且不能准确地预测真实的纺织品的行为。 在这个项目中,PI团队将比较外观和变形模型与CT,成像和其他方式的纺织品测量结果,然后根据需要对其进行改进,以便它们能够拟合真实的材料。 目前的方法不能很好地捕捉现有织物的性质,以预测其外观下密切的视觉检查。 PI团队将开发新的方法,用于联合捕获纺织品的外观和机械性能,将测量和模型调整相结合,以生成纺织品及其服装和家具的预测工作模型。 详细的布料模拟和渲染目前对于中等复杂的对象(如完整的服装)是不切实际的。 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团队将创建多尺度模型,以便在设计过程中实现交互式预测可视化。 由于目标应用都需要准确的预测,研究的主要重点是验证,测试各个技术部分的准确性和新技术在实际使用中的最终实用性。

项目成果

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