CAREER: Efficient and Realistic Spatial/Temporal Appearance Details
CAREER: Efficient and Realistic Spatial/Temporal Appearance Details
批准号:
0132970
负责人:
Yizhou Yu
金额:
$32.5万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-01-15 至 2006-12-31
中文摘要
这个项目解决了恢复和综合生成逼真外观细节的问题。外观细节包括颜色/反射率的变化,3D表面上的小几何特征,以及这些高分辨率几何和物理属性在不同时间的变化。我们将这些细节称为3D和时间纹理,而不是2D纹理,后者在2D空间中只有颜色变化。本项目描述了围绕3D和时间纹理的四类问题的基础研究:(1)考虑3D时空变化细节的纹理建模的统一框架的发展;(2)从照片和视频中恢复高质量外观细节或综合生成它们的新算法的发展;(3)能够从给定实例生成3D和时间纹理的新实例的高效合成算法的发展;(4)3D和时间纹理的高效表示和压缩方案的研究。该项目将在3D和时间外观建模和合成方面取得重大进展,从而导致通过图形方法产生的合成图像的整体质量的提高。3D和时间纹理是几何建模和物理模拟的补充。解决提出的问题将极大地有利于这些和其他相关研究方向。在基于物理的模拟方面的最新进展使得通过求解光传输和运动方程来生成合成图像成为可能。虽然这些基于模拟的技术非常昂贵,但从这些技术生成的结果通常被发现过于干净和平滑,看起来不够逼真。将外观细节结合到这些方法中将是非常可取的。同时,最新的基于图像和激光距离扫描的几何重建技术使得获得高质量的几何模型成为可能。外观建模在计算机图形学应用中变得越来越重要,其中细节的高效和逼真表示是必不可少的。这项工作将能够以有效的方式产生统计上正确的、物理上可信的外观细节。在电影业,高质量的头发模型和皮肤表面细节将极大地缩小合成角色和真实角色之间的差距。在游戏行业,实时3D和时间纹理将使虚拟环境更接近现实一大步。这一点适用于大量的应用,包括电子商务、电视和网络内容制作、人机交互、建筑和考古演练。总而言之,该项目的预期结果将是开发出重要的新技术和成果,为现实世界的应用程序提供有用的解决方案,计算机图形学与其他相关领域(如图像处理和计算机视觉)之间的相互促进,以及课程创新。
英文摘要
0132970Yu, YizhouU of Ill - ChampaignThis project addresses the problem of recovering and synthetically generating realistic appearance details. Appearance details include color/reflectance variations, small geometric features on 3D surfaces, and the change of these high-resolution geometric and physical properties at different times. We call these details 3D and temporal textures in contrast to 2D textures which only have color variations in a 2D space. This project describes fundamental research in four classes of problems surrounding 3D and temporal textures:(1) the development of a unified framework for texture modeling considering 3D spatially and temporally varying details;(2) the development of novel algorithms that either recover high-quality appearance details from photographs and videos or generate them synthetically;(3) the development of efficient synthesis algorithms that can generate novel instances of 3D and temporal textures from given examples;(4) the investigation of efficient representation and compression schemes for 3D and temporal textures.This project will result in significant advances in 3D and temporal appearance modeling and synthesis, and therefore lead to overall qualitative improvement of the synthetic imagery created by graphics approaches.3D and temporal textures complement geometric modeling and physical simulation. Addressing the proposed problem will greatly benefit these and other related research directions. Recent advances in physics-based simulation made it possible to generate synthetic imagery from solving light transport and motion equations. While these simulation-based techniques are quite expensive, the results generated from these techniques are often found to be too clean and smooth to look realistic enough. Incorporating appearance details into these methods would be highly desirable. Meanwhile, recent geometric reconstruction techniques from images and laser range scans have made it possible to acquire high-quality geometric models. Appearance modeling is becoming increasingly important in computer graphics applications where the efficient and realistic representation of details is essential. This work will be able to produce statistically correct, physically plausible appearance details in an efficient manner. In the film industry, high-quality hair models and skin surface details will dramatically shrink the gap between synthetic and real characters. In the game industry, real-time 3D and temporal textures will bring virtual environments a large step closer to reality. This holds true for a large number of applications including electronic commerce, TV and Web content production, human computer interaction, architectural and archeological walkthroughs.Altogether, the expected outcome of the project will be the development of important new techniques and results that provide real-world applications with useful solutions, cross-fertilization between computer graphics and other related areas (such as image processing and computer vision), and curricular innovations.
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会议论文
III: Small:Collaborative Research: Coordinated Visualization for Comparative Analysis of Cross-Subject, Multi-Measure, Multi-Dimensional Brain Imaging Data
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批准号:0914631
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项目类别:Standard Grant
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资助金额:$25.0万
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财政年份:2009
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负责人:Yizhou Yu
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依托单位:
海外基金