CGV: Small: Collaborative Research: Immersive Visualization and 3D Interaction for Volume Data Analysis

CGV：小型：协作研究：用于体数据分析的沉浸式可视化和 3D 交互

• 批准号: 1319606
• 负责人: David Laidlaw
• 金额: $ 25万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319606&HistoricalAwards=false
• 关键词: CGV; Small; Collaborative; Research; Immersive

This collaborative research project (IIS-1320046, IIS-1319606) designs a 3-dimensional immersive visualization environment for volume data that is critical in a variety of application domains, such as medicine, engineering, geophysical exploration, and biomechanics. For example, biomechanics researchers examine volumes derived from insect scans to understand how form relates to function, particularly in regard to how insects create internal fluid flows. For effective analysis of a 3D volume, scientists and other users need to integrate various views, peer inside the volume, and separate various structures in the data. However, despite many advances in volume rendering algorithms, neither traditional displays nor traditional interaction techniques are sufficient for efficient and accurate analysis of complex volume datasets. This project develops an approach for interactively exploring and segmenting volume datasets by combining and extending: (1) utilization of advanced, high-fidelity displays based on virtual reality (VR) technologies for improving the visual analysis of volume data, and (2) the use of natural, gesture-based 3D techniques. Using controlled, empirical studies with real-world volume datasets from biomechanics and other biological sciences, the investigators are determining what characteristics of advanced displays can lead to faster, more accurate visual analysis. Iterative design and evaluation methods are being used to develop usable and natural 3D interaction techniques with which users can explore the interior of volume datasets. Beyond the empirical findings of these studies, an important outcome of the project is the design of a next-generation volume data analysis system that can be used by scientists and researchers to improve the efficiency and accuracy of their work.The expected results will provide a deep understanding of visualization principles fostering further advancements in the realm of volume data analysis. Easier, more accurate, and faster analysis can lead to improvements in healthcare, breakthroughs in science, and advances in education. For example, this work may lead to insights into fundamental physiological mechanisms of feeding, breathing, and circulation in insects - one of the most important animal groups on earth. There are millions of insect species living in almost every habitat, and their lifestyles have profound impacts on human societies. Their effects in areas such as agriculture and health can be both positive (e.g., pollination) and negative (e.g., crop damage, disease), and understanding their fundamental physiologies is critical to controlling their impact. The project provides opportunities for interdisciplinary educational and research activities for graduate and undergraduate students, and outreach activities to underrepresented students. The results of this work will be disseminated broadly via publication in archival journals, peer-reviewed conferences, and online forums. The project website (https://research.cs.vt.edu/3di/node/188) will provide access to research results, including data sets and software.

这个合作研究项目（IIS-1320046，IIS-1319606）设计了一个三维沉浸式可视化环境的体积数据，是在各种应用领域，如医学，工程，地球物理勘探和生物力学的关键。例如，生物力学研究人员检查了从昆虫扫描中获得的体积，以了解形式与功能的关系，特别是关于昆虫如何产生内部流体流动。为了有效分析3D体积，科学家和其他用户需要集成各种视图、观察体积内部并分离数据中的各种结构。然而，尽管在体绘制算法的许多进步，无论是传统的显示器，也不是传统的交互技术是足够的复杂的体积数据集的有效和准确的分析。该项目开发了一种交互式探索和分割体积数据集的方法，通过组合和扩展：（1）利用基于虚拟现实（VR）技术的先进高保真显示器来改善体积数据的视觉分析，以及（2）使用自然的基于手势的3D技术。通过对来自生物力学和其他生物科学的真实世界体积数据集进行对照、实证研究，研究人员正在确定先进显示器的哪些特性可以带来更快、更准确的视觉分析。迭代设计和评估方法被用于开发可用的和自然的3D交互技术，用户可以探索体积数据集的内部。除了这些研究的实证结果之外，该项目的一个重要成果是设计了下一代体数据分析系统，可供科学家和研究人员使用，以提高工作效率和准确性。预期结果将提供对可视化原理的深入理解，促进体数据分析领域的进一步发展。更快、更准确和更快的分析可以改善医疗保健、科学突破和教育进步。例如，这项工作可能会导致对昆虫进食，呼吸和循环的基本生理机制的见解-地球上最重要的动物群体之一。有数以百万计的昆虫物种生活在几乎每一个栖息地，它们的生活方式对人类社会有着深远的影响。它们在农业和卫生等领域的影响可能是积极的（例如，授粉）和阴性（例如，作物损害、疾病），了解它们的基本生理机能对于控制它们的影响至关重要。该项目为研究生和本科生提供跨学科教育和研究活动的机会，并为代表性不足的学生提供外联活动。这项工作的结果将通过在档案期刊、同行评议会议和在线论坛上发表广泛传播。该项目网站（https：//research.cs.vt.edu/3di/node/188）将提供研究结果，包括数据集和软件。