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: $ 45万
• 依托单位: Cornell University
• 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
• 起止时间: 2007-02-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0644175&HistoricalAwards=false
• 关键词: CAREER; Scalable; Rendering; Visual; Realism

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.

职业：计算机图形学的一个基本挑战是创建交互式虚拟环境，准确地描绘真实的世界的复杂自然场景。 这些虚拟环境对于各种应用至关重要，包括电子商务、教育、工业设计和建筑规划、游戏和电影、安全分析和虚拟培训以及文化遗产。 真实地模拟真实的世界的视觉外观极具挑战性，因为感兴趣的场景具有复杂的几何形状、材料和照明，在广泛的物理尺度上相互作用，从毫米大小的表面凹凸到大型结构。我们称这样的场景为尺度复杂。 目前的渲染方法对比例是盲目的，使得在这种比例复杂的场景中真实地模拟光反射和散射的复杂路径沿着是不可行的。 这个项目开发了一个新的框架，用于真实地渲染尺度复杂场景的图像。重要的是，该框架支持丰富的光照现象和渲染效果，如间接光照、参与介质、次表面散射、运动模糊和景深等，即使场景和模拟光照现象的复杂性不断增加，该框架也必须具有良好的可扩展性。该项目探讨了以下新方法：（a）对所有照明现象和渲染效果的统一处理，（B）与基于早期视觉和更高级视觉的感知度量耦合的新颖的多分辨率表示，以消除在视觉上不重要的计算，（c）用于根据需要精确计算照明细节的新方法，具有照明驱动的几何和材料简化，以及（d）用于交互性能的新的混合CPU/GPU算法。