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.

该协作研究项目（IIS-1320046，IIS-1319606）设计了一个3维的沉浸式可视化环境，用于数量数据，这对于各种应用领域，例如医学，工程，地球物理探索和生物力学至关重要。例如，生物力学研究人员检查了昆虫扫描得出的量，以了解形式与功能的关系，尤其是关于昆虫如何产生内部液体流动的关系。为了有效地分析3D卷，科学家和其他用户需要整合各种视图，在卷中进行凝视，并分离数据中的各种结构。但是，尽管渲染算法的数量有很多进展，但传统显示器和传统交互技术都不足以有效，准确地分析复杂的体积数据集。该项目开发了一种通过组合和扩展来进行交互探索和分割卷数据集的方法：（1）基于虚拟现实（VR）技术的高级，高效率显示，以改善体积数据的可视化分析，以及（2）使用自然，基于姿态的3D 3D技术。使用来自生物力学和其他生物科学的实际体积数据集的受控的经验研究，研究人员正在确定高级显示的特征可以导致更快，更准确的视觉分析。迭代设计和评估方法正在用于开发可用且天然的3D交互技术，用户可以探索卷数据集的内部。除了这些研究的经验发现之外，该项目的重要结果是设计下一代数量数据分析系统的设计，科学家和研究人员可以使用该系统来提高其工作的效率和准确性。预期的结果将对可视化原则有深入的了解，从而促进数量数据分析领域的进一步进步。更容易，更准确，更快的分析可以改善医疗保健，科学的突破以及教育进步。例如，这项工作可能会导致人们对昆虫中喂养，呼吸和循环的基本生理机制的见解，昆虫是地球上最重要的动物群体之一。几乎每个栖息地都有数百万种昆虫物种，它们的生活方式对人类社会产生了深远的影响。它们在农业和健康等领域的影响既可以是积极的（例如，授粉）和负面的（例如农作物损害，疾病），并且了解其基本生理学对于控制其影响至关重要。该项目为研究生和本科生提供了跨学科的教育和研究活动的机会，并为代表性不足的学生提供了外展活动。这项工作的结果将通过档案期刊，同行评审会议和在线论坛的出版物进行广泛传播。项目网站（https://research.cs.vt.edu/3di/node/188）将提供对研究结果的访问，包括数据集和软件。