ITR: Collaborative Research: Image-Based Rendering in Forensic Reconstruction and Historical Preservation

ITR：协作研究：法医重建和历史保护中基于图像的渲染

• 批准号: 0205324
• 负责人: David Luebke
• 金额: $ 24.82万
• 依托单位: University of Virginia Main Campus
• 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
• 起止时间: 2002-10-01 至 2006-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205324&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; Image; Based

Valuable information about the world around us is being lost. Every day we lose information of both current and historical significance, simply because it is too difficult to capture 3D models of our environment. Today, such models are primarily created by hand, making measurements with tape measures and entering the results manually. Even after models are constructed, we do not know the best ways to visualize them effectively.This research proposes to design and develop an end-to-end solution to the problem of documentation, dissemination, and display of real-world environments. To focus the research, two driving problems are targeted: forensic science and education. This research brings together an interdisciplinary team including the law enforcement community, the Federal Bureau of Investigation and the Armed Forces Institute of Pathology. Additionally, one of our team members, from the New Orleans Museum of Art, is directing a major exhibition in which we propose to include a virtual environment of Monticello, President Jefferson's home.We will tackle the problems of acquiring, processing, representing, rendering and display of real- world data, focusing on the two target applications. Our goal is to design and build a complete end-to-end prototype system. The work includes:Acquisition. We will mount an accurate rangefinder on a motorized cart and tackle the problem of capturing as complete a model as possible. This requires accurate tracking and a solution to the next best view problem in a practical sense, including resolution, reflectance, and importance of the surfaces.Processing. A very difficult problem is the registration of color with depth data, and of scans from multiple locations. We will develop algorithms to robustly register the data, and filter to reduce outliers and noise.Representation. We will develop algorithms to process the massive amounts of data (100 MB per scan, tens of scans per room) into both efficient geometric and image-based representations. We will compare and contrast the representations in terms of quality and efficiency.Rendering. We will develop hierarchical and out-of-core algorithms to render the image- based and geometric models at interactive rates, and research perceptually driven rendering techniques to maximize rendering efficiency.Display. This is perhaps the most difficult part of the problem because it involves the way humans perceive the environment. We will develop a hybrid projector/head-mounted-display system to provide stereo views to multiple viewers in a life-sized walking environment. The goal is to give the participants a sense of presence, of being in Mr. Jefferson's house.

关于我们周围世界的宝贵信息正在丢失。每天我们都会失去当前和历史意义的信息，仅仅是因为捕获环境的3D模型太难了。如今，此类模型主要是通过手工创建的，通过磁带测量进行测量并手动输入结果。即使在构建模型之后，我们也不知道有效地可视化它们的最佳方法。本研究建议设计和开发端到端解决文档，传播和展示现实环境问题的解决方案。为了集中研究，两个驾驶问题是针对的：法医学和教育。这项研究汇集了一个跨学科团队，包括执法界，联邦调查局和武装部队病理研究所。此外，我们来自新奥尔良艺术博物馆的团队成员之一正在指导一个大型展览，我们建议我们包括蒙蒂塞洛（Monticello）的虚拟环境，总统杰斐逊（Jefferson）的家。并显示现实世界数据，重点关注两个目标应用程序。我们的目标是设计和建立一个完整的端到端原型系统。工作包括：收购。我们将在电动推车上安装一个精确的测距仪，并解决捕获尽可能完整模型的问题。这需要在实际意义上进行准确的跟踪和解决下一个最佳视图问题的解决方案，包括表面的分辨率，反射和重要性。一个非常困难的问题是对颜色的注册以及深度数据的注册以及来自多个位置的扫描。我们将开发算法以鲁棒性注册数据，并过滤以减少异常值和噪声。我们将开发算法，以将大量数据（每次扫描100 MB，每个房间的扫描100 MB）处理为有效的几何表示和基于图像的表示形式。我们将在质量和效率方面比较和对比表示。我们将开发层次结构和核心外算法，以交互式速率呈现基于图像的和几何模型，并研究以感知驱动的渲染技术来最大程度地提高渲染效率.display。这也许是问题中最困难的部分，因为它涉及人类感知环境的方式。我们将开发一个混合投影仪/头部播放系统，以在真人大小的步行环境中为多个观众提供立体看法。目的是让参与者在杰斐逊先生的家中有一种存在感。