Collaborative Research: Fundamentals and Algorithms for Streaming Meshes

协作研究：流网格的基础知识和算法

• 批准号: 0429901
• 负责人: Jack Snoeyink
• 金额: $ 27.96万
• 依托单位: University of North Carolina at Chapel Hill
• 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: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0429901&HistoricalAwards=false
• 关键词: Collaborative; Research; Fundamentals; Algorithms; Streaming

Abstract for proposal 0429901/0430065Modern technology enables the creation of digital 3D polygon meshes with incredible detail. Current mesh formats, which were designed when models and meshes were orders of magnitude smaller, complicate the processing of large, detailed data. This project will fully develop a new streaming mesh representation, and use it as a framework for algorithms that produce and/or consume large polygonal and polyhedral meshes. At its core are several simple, new ideas that get around current limitations in computer memory hierarchies. The immediate benefit of compressed storage, faster loading, and better memory use appeal to any application creating large models, including scientific and engineering visualization for data exploration, scanned artifacts for artistic and museum displays, landscape modeling for flood or fire control, mesh generation for scientific computing, virtual environments for collaboration and education, and 3D models for e-commerce. This project identifies the parameters that characterize a streaming mesh, then designs and implements algorithms whose behavior can be analyzed in terms of these parameters. Initial algorithms include surface simplification, compression, and transmission for geometric models for computer graphics, and extend to include 2D and 3D stream-based Delaunay triangulators. The key ideas grew out of work on geometric models in computer graphics; the project's investigators will apply them in more general contexts. The result will be useful software, embodying a computation paradigm that can process arbitrarily large meshes while avoiding geometric artifacts, degradation of quality, and other difficulties of approaches that cut meshes into pieces to fit into available memory. This project will ensure its broader impact though distribution of software (both source code and executables) for streaming and compressing meshes, and stream-based 2D and 3D Delaunay triangulation. The project will impact education of undergraduate and graduate students, and reach out to high school and elementary students through demonstration days. The principle investigators use several means to reach groups that are underrepresented in computer science.

提案摘要 0429901/0430065现代技术能够创建具有令人难以置信的细节的数字 3D 多边形网格。当前的网格格式是在模型和网格小几个数量级时设计的，使大型详细数据的处理变得复杂。该项目将全面开发一种新的流式网格表示，并将其用作生成和/或消耗大型多边形和多面体网格的算法框架。其核心是几个简单的新想法，可以克服当前计算机内存层次结构的限制。压缩存储、更快的加载和更好的内存使用的直接好处对任何创建大型模型的应用程序都有吸引力，包括用于数据探索的科学和工程可视化、用于艺术和博物馆展示的扫描文物、用于洪水或消防的景观建模、用于数据挖掘的网格生成。科学计算、协作和教育虚拟环境以及电子商务 3D 模型。该项目识别表征流网格的参数，然后设计并实现可以根据这些参数分析其行为的算法。初始算法包括计算机图形几何模型的表面简化、压缩和传输，并扩展到包括基于 2D 和 3D 流的 Delaunay 三角测量器。关键思想源自对计算机图形学中几何模型的研究；该项目的研究人员将把它们应用到更一般的环境中。结果将是有用的软件，体现了一种计算范式，可以处理任意大的网格，同时避免几何伪影、质量下降以及将网格切成碎片以适合可用内存的方法的其他困难。该项目将通过分发用于流式传输和压缩网格以及基于流的 2D 和 3D Delaunay 三角测量的软件（源代码和可执行文件）来确保其更广泛的影响。该项目将影响本科生和研究生的教育，并通过示范日惠及高中生和小学生。主要研究人员使用多种方法来接触计算机科学领域代表性不足的群体。