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CAREER: Scalable Rendering for Visual Realism in Scale-Complex Scenes

CAREER: Scalable Rendering for Visual Realism in Scale-Complex Scenes
职业:在规模复杂的场景中实现视觉真实感的可扩展渲染
批准号:
0644175
负责人:
Kavita Bala
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-02-01 至 2013-01-31

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中文摘要
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英文摘要
CAREER: Scalable Rendering for Visual Realism in Scale-Complex ScenesPI: Kavita BalaA fundamental challenge in computer graphics is to create interactive virtual environments that accurately depict the complex natural scenes of the real world. These virtual environments are vital for a wide variety of applications, including e-commerce, education, industrial design and architectural planning, games and movies, safety analysis and virtual training, and cultural heritage. Realistically simulating the visual appearance of the real world is extremely challenging because scenes of interest have complex geometry, material, and lighting interacting across a wide range of physical scales, ranging from millimeter-sized surface bumps to large-scale structure. We call such scenes scale-complex. Current rendering methods are blind to scale, making it infeasible to realistically simulate the complex paths along which light reflects and scatters in such scale-complex scenes. This project develops a novel framework for realistically rendering images of scale-complex scenes. Importantly, the framework supports rich illumination phenomena and rendering effects such as indirect illumination, participating media, subsurface scattering, motion blur, and depth-of-field.For the proposed framework to be scalable, it must perform well even with growing complexity of the scene and of simulated illumination phenomena. This project explores the following new approaches: (a) a unified treatment of all illumination phenomena and rendering effects, (b) novel multiresolution representations coupled with perceptual metrics based on early vision and higher level vision to eliminate computation where it is not visually important, (c) new methods for accurately computing illumination detail as needed, with illumination-driven simplification of geometry and material, and (d) new hybrid CPU/GPU algorithms for interactive performance.
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CHS: Medium: Collaborative Research: Physics and Learning Integration Using differentiable rendering
  • 批准号:
    1900783
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2019
  • 负责人:
    Kavita Bala
  • 依托单位:
CHS: Small: Data-Driven Material Understanding and Decomposition
  • 批准号:
    1617861
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.42万
  • 财政年份:
    2016
  • 负责人:
    Kavita Bala
  • 依托单位:
CGV: Medium: Collaborative Research: Understanding Translucency: Physics, Perception, and Computation
  • 批准号:
    1161645
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $39.83万
  • 财政年份:
    2012
  • 负责人:
    Kavita Bala
  • 依托单位:
CPA -G&V: Collaborative Research: Visual Equivalence: a New Foundation for Perceptually-Based Rendering of Complex Scenes
  • 批准号:
    0811680
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.5万
  • 财政年份:
    2008
  • 负责人:
    Kavita Bala
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis