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: 0347740
• 负责人: Doug James
• 金额: $ 40万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-15 至 2007-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347740&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-0347740DEFORMANE现象是我们生活中不可或缺的一部分；它影响了我们的外观（例如，皮肤，头发），我们发出的声音（例如，衣服，声带），自然界的美丽（例如，风在风中吹森林）以及重要的决定（例如，医疗计划）。变形建模取得了巨大的进步，但我们仍然希望越来越现实的几何和动态复杂性。 变形在虚拟环境的多模式反馈中也起着重要作用：使用触觉界面感受接触力，看到阴影和反射的现实变形外观以及听到触点声音。不仅需要在高速率下进行准确的变形，而且这种现象也可能非常复杂。实时互动性和复杂的大规模模拟的需求相互矛盾，一种逻辑算法策略是尽可能提前做尽可能多的工作。利用大规模的预先计算和数据驱动的制表非常有吸引力，但是如何做到这一点，在多大程度上，对于大多数非线性系统来说，这仍然是一个谜。然而，初步证据表明，潜在的预先摄入速度很容易是一百万倍。 通过研究当今的预算技术，我们将利用百万倍的速度来在明天的超级计算机上进行多模式模拟。我们的科学目标是了解如何系统地预先计算，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）基于减少的坐标表示，数据驱动的可变形模型的预抄写技术； （2）实时``播放''的复杂运动的可变形运动数据库；'（3）交互式仿真的多模式方面，包括触觉渲染，数据驱动的可变形声音模型和预先计算的可变形对象外观模型。 我们的研究是由现实世界应用驱动的，将在交互式计算机动画，虚拟医学，机器人技术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。