CAREER: Precomputing Data-driven Deformable Systems for Multimodal Interactive Simulation

职业：预计算数据驱动的可变形系统以进行多模态交互仿真

• 批准号: 0652597
• 负责人: Doug James
• 金额: --
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0652597&HistoricalAwards=false
• 关键词: CAREER; Precomputing; Data; driven; Deformable

James, DougCarnegie Mellon UniversityCCF-0347740Deformation phenomena are a rich and integral part of our lives; it affects our appearance (e.g., skin, hair), the sounds we make (e.g., clothing, vocal cords), beauty in nature (e.g., a forest blowing in the wind), and important decisions (e.g., medical planning). Deformation modeling has made enormous progress, but we still desire increasingly realistic levels of geometric and dynamic complexity. Deformation also plays an important role in multimodal feedback for virtual environments: feeling contact forces using haptic interfaces, seeing realistic deformable appearances with shadows and interreflections, and hearing contact sounds. Not only are accurate deformations required at high rates, but the phenomena can also be extremely complex.Given the conflicting demands of real-time interactivity and complex large-scale simulation, one logical algorithmic strategy is to do as much work ahead of time as possible. Exploiting massive precomputation and data-driven tabulation is appealing, but how this can be done, and to what extent, remains a mystery for most nonlinear systems. Nevertheless, preliminary evidence suggests that potential precomputation speedups are easily a million-fold. By researching precomputation techniques today, we stand to exploit million-fold speedups for multimodal simulation on supercomputers of tomorrow.Our scientific objective is to understand how to systematically precompute, simulate and experience data-driven models of large-scale nonlinear deformable systems. We address these goals in three ways: (1) precomputation techniques for data-driven deformable models based on reduced coordinate representations; (2) deformable motion databases of complex motions for real-time ``playback;'' (3) multimodal aspects of interactive simulation, including haptic rendering of contact forces, data-driven deformable sound models, and precomputed deformable object appearance models. Our research is driven by real-world applications, and will be explored in the broad context of interactive computer animation, virtual medicine, robotics and manufacturing, and simulation of large-scale natural environments.

James，DougCarnegie Mellon UniversityCCF-0347740变形现象是我们生活中丰富而不可分割的一部分;它影响我们的外观（例如，皮肤，头发），我们发出的声音（例如，衣服，声带），自然美（例如，在风中吹的森林），以及重要的决定（例如，医疗规划）。变形建模已经取得了巨大的进步，但我们仍然希望越来越逼真的几何和动态复杂性。 变形在虚拟环境的多模态反馈中也起着重要的作用：使用触觉界面感受接触力，看到具有阴影和相互反射的真实可变形外观，以及听到接触声音。不仅需要高速率的精确变形，而且现象也可能非常复杂。考虑到实时交互性和复杂的大规模模拟的冲突需求，一个合乎逻辑的算法策略是尽可能提前完成工作。利用大规模的预计算和数据驱动的制表是很有吸引力的，但如何做到这一点，以及在多大程度上，仍然是大多数非线性系统的一个谜。然而，初步证据表明，潜在的预计算加速很容易达到百万倍。 通过研究当前的预计算技术，我们将为未来的超级计算机上的多模态模拟开发百万倍的加速比。我们的科学目标是了解如何系统地预计算，模拟和体验大规模非线性可变形系统的数据驱动模型。 我们以三种方式解决这些目标：（1）基于简化坐标表示的数据驱动可变形模型的预计算技术;（2）用于实时“回放”的复杂运动的可变形运动数据库;（3）交互式仿真的多模态方面，包括接触力的触觉渲染，数据驱动可变形声音模型和预计算的可变形物体外观模型。 我们的研究是由现实世界的应用驱动，并将在交互式计算机动画，虚拟医学，机器人和制造，以及大规模自然环境的模拟的广泛背景下进行探索。