ITR: Visualization and Interaction with Large Graphics Datasets over Networks

ITR：通过网络与大型图形数据集进行可视化和交互

• 批准号: 0081847
• 负责人: Amitabh Varshney
• 金额: $ 45万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0081847&HistoricalAwards=false
• 关键词: ITR; Visualization; Interaction; Large; Graphics

The last decade has witnessed a significant research thrust aimed at handling very large models in computer graphics. This project will extend those efforts by focusing on means to efficiently visualize, interact with, and manipulate large-scale graphics datasets over networks. The PI plans to develop techniques that will decrease latency, reduce bandwidth, and increase the interactivity for large graphics datasets over networks. The technical vision is to build a distributed rendering system that (a) takes advantage of the respective powers of image-based and object-based rendering for visualization of large-scale graphics datasets, (b)is well-suited for visualization-assisted collaboration and interaction across limited bandwidth links, and (c) takes into account the client, server, and network resources to deliver the best overall performance including times to transfer and render a dataset. Towards these ends the PI will explore techniques for high compression, progressive transmission, rendering from compressed data, handling time-varying datasets, and resource- aware rendering. The project work plan also seeks to develop tools for annotation, navigation, and sharing of educational spaces for use in synchronous and asynchronous learning environments that use three-dimensional datasets. This research will help push network-based collaborative design to the next level in a variety of science, engineering, and medical applications.

在过去的十年中，已经见证了一个重要的研究推力，旨在处理非常大的模型，在计算机图形学。该项目将通过专注于有效地可视化，交互和操纵网络上的大规模图形数据集的方法来扩展这些努力。PI计划开发技术，以减少延迟，减少带宽，并增加网络上大型图形数据集的交互性。技术愿景是构建一个分布式渲染系统，该系统（a）利用基于图像和基于对象的渲染的各自能力来实现大规模图形数据集的可视化，（B）非常适合于跨有限带宽链路的可视化辅助协作和交互，以及（c）考虑客户端、服务器、和网络资源来提供最佳的整体性能，包括传输和呈现数据集的时间。为了实现这些目标，PI将探索高压缩，渐进传输，压缩数据渲染，处理时变数据集和资源感知渲染的技术。该项目工作计划还寻求开发用于注释、导航和共享教育空间的工具，以用于使用三维数据集的同步和异步学习环境。这项研究将有助于推动基于网络的协同设计在各种科学，工程和医疗应用到一个新的水平。