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Real-time synthesis and capture of contact rich human interactions

Real-time synthesis and capture of contact rich human interactions
实时合成和捕捉丰富的人类互动
批准号:
RGPIN-2018-05723
负责人:
Andrews, Sheldon
金额:
$1.68万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
介绍******运动合成的虚拟人物涉及计算旋转和关节位置为一个铰接的三维(3D)结构,或骨架。这样的例子在现代计算机图形应用程序中无处不在,例如视频游戏、视觉效果和虚拟现实(VR)。近年来,角色动作的自动合成已经取得了很大的进步,但这些方法仍然无法达到真人的技能水平和身体交互性。众所周知,攀爬、翻滚和灵巧的操作等动作很难合成;追踪和重建这些运动同样困难。******接触是这些环境中的一个重要因素,必须给予特别考虑。物理模型可以用来提高真实感,但由于非线性和与复杂物理模拟相关的开销,鲁棒性和计算性能成为关注的问题。因此,物理角色的自动合成方法的适用范围有限,因此电子游戏和VR开发者采用它们的速度很慢。******目的******我的研究重点是虚拟人物的运动合成,其中运动需要大量的物理交互或接触。由于严格的帧率要求,将会有一个特别的努力来开发具有有限计算预算的实时应用程序的方法。我在未来五年内开发的技术将为3D角色的熟练动作合成提供新的方法,提供前所未有的交互性,可以与真人的保真度相媲美。为此,我将探讨三个平行但互补的轨道:******1。快速稳定的接触物理模拟;***2。复杂物理交互的数据集和数据驱动方法;***3。虚拟角色鲁棒运动合成。******我的预期研究结果将是交互式角色动画,运动规划,物理模拟和运动重建的创新方法。在此过程中发现的解决方案将具有直接的实际意义。这不仅会带来游戏角色动画的新技术,还会影响机器人模拟、VR训练和性能捕捉应用。长期影响将是各方面进展的倍增。******科学方法******我一般的科学方法是在适当的地方用数据驱动的方法来增加物理模拟。这包括收集真实世界的例子来构建封装自然现象的参数化模型。这样的模型可以用来指导涉及物理模拟的优化。由于我的研究重点是实时应用,模型约简技术也是必不可少的组成部分。挑战在于在不影响整体保真度的情况下近似物理行为。
英文摘要
INTRODUCTION******Motion synthesis for virtual characters involves computing rotations and joint positions for an articulated three-dimensional (3D) structure, or skeleton. Examples of this are ubiquitous in modern computer graphics applications, such as video games, visual effects, and virtual reality (VR). Large strides have been made in recent years on the automatic synthesis of motion for characters, yet methods still fail to achieve the level of skill and physical interactivity of real humans. Motions such as climbing, tumbling, and dexterous manipulation are notoriously difficult to synthesize; tracking and reconstructing these motions is similarly difficult.******Contact is an important factor in these settings and must be given special consideration. Physical models can be used to improve realism, but robustness and computational performance become concerns due to the non-linearities and overhead associated with complex physical simulations. Automatic synthesis methods for physical characters are therefore limited in their scope, and as such video game and VR developers have been slow to adopt them.******OBJECTIVE******My research focuses on motion synthesis of virtual characters where the motion demands significant amounts of physical interaction, or contact. There will be a special effort to develop methods for real-time applications with a limited computational budget due to strict framerate requirements. The techniques I develop over the next five years will give rise to new ways for skilled motion synthesis for 3D characters, offering unprecedented interactivity that rivals the fidelity of real humans. For this purpose, I will pursue three parallel, but complementary, tracks:******1. Fast and stable physical simulations involving contact;***2. Datasets and data-driven methods for complex physical interaction;***3. Robust motion synthesis for virtual characters.******The anticipated results of my research will be innovative methods for interactive character animation, motion planning, physics simulation, and motion reconstruction. Solutions uncovered along the way will have immediate practical implications. This will result not only in novel technology for character animation in games, but will also impact robotics simulation, VR training, and performance capture applications. The long-term impact will be a multiplication of progress across all tracks.******SCIENTIFIC APPROACH******My general scientific approach is to augment physical simulations with data-driven methods where appropriate. This includes collecting real-world examples to build parameterized models that encapsulate natural phenomena. Such models may then be used to guide an optimization involving physics simulation. Since my research focuses on real-time applications, model reduction techniques are also an essential component. Challenges lie in approximating physical behaviour without compromising overall fidelity.
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Real-time synthesis and capture of contact rich human interactions
  • 批准号:
    RGPIN-2018-05723
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.68万
  • 财政年份:
    2022
  • 负责人:
    Andrews, Sheldon
  • 依托单位:
Data-driven Friction Models for Simulation and Material Fabrication
  • 批准号:
    571411-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.28万
  • 财政年份:
    2021
  • 负责人:
    Andrews, Sheldon
  • 依托单位:
Real-time synthesis and capture of contact rich human interactions
  • 批准号:
    RGPIN-2018-05723
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.68万
  • 财政年份:
    2021
  • 负责人:
    Andrews, Sheldon
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  • 财政年份:
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  • 负责人:
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