ITR: Visualization and Interaction with Large Graphics Datasets over Networks

过去的十年见证了一项旨在处理计算机图形中的非常大的模型的重大研究推力。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计划开发减少延迟、减少带宽并提高网络上大型图形数据集的互动性的技术。技术愿景是构建一种分布式渲染系统，该系统(A)利用基于图像和基于对象的渲染的各自的能力来可视化大规模图形数据集，(B)非常适合于在有限带宽链路上的可视化辅助协作和交互，以及(C)考虑客户端、服务器和网络资源以提供最佳的整体性能，包括传输和渲染数据集的时间。为了达到这些目的，PI将探索用于高压缩、渐进传输、从压缩数据渲染、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，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、工程和医疗应用中更上一层楼。

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.