Computer Graphics Tools for Understanding Tensor-Valued Volume Data: A Painting Metaphor

用于理解张量值体积数据的计算机图形工具：绘画隐喻

• 批准号: 9619649
• 负责人: David Laidlaw
• 金额: $ 13.96万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-03-15 至 1999-03-22
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9619649&HistoricalAwards=false
• 关键词: Computer; Graphics; Tools; Understanding; Tensor

This multi-disciplinary research project will investigate, apply, and evaluate new computer graphics tools for understanding vector- and second-order tensor-valued volume data. The efficacy of the tools will be evaluated by the extent to which they generate insight into several specific physical phenomena: fully-developed turbulent flow, the progression of disease in a mouse analogue of multiple sclerosis, and the neonatal development of the mouse brain. The application of the new techniques and collaboration with researchers in other fields provides the opportunity to validate the techniques and ensure that they are responsive in addressing the scientific problems. The techniques will be developed using a painting metaphor. For centuries artists have used a divide-and-conquer approach to creating paintings, representing different aspects of a scene in different layers of paint. In addition, artists use brush strokes, with their many characteristics of texture, size, shape, color, and opacity, to represent important features of a scene on a canvas, depicting the essence of the scene and eliminating unnecessary detail. Both techniques, and the collective artistic experience in using them, can be applied to computer graphics in the context of displaying volume data. Techniques for understanding vector-valued and tensor-valued volume data stand to benefit particularly, because volumes contain so much information and because tensor and vector values have many relevant, interdependent aspects. Existing techniques are limited in their ability to abstract the data effectively and to display the many relevant aspects of the data simultaneously, but the new techniques will address both of these problems. As a result, they will be more effective in generating insight into the physical phenomena measured as well as in communicating the insight. Because the techniques will be developed with application to three specific problems in two disciplines, they are likely t o have broader application.

这个多学科研究项目将调查，应用和评估新的计算机图形工具，以了解矢量和二阶张量值数据。 该工具的功效将通过对几种特定物理现象的洞察力进行评估：完全发达的湍流，多发性硬化症小鼠类似物中疾病的进展以及小鼠脑的新生儿发育。 新技术的应用和与其他领域的研究人员合作提供了验证这些技术并确保它们在解决科学问题方面做出反应的机会。 这些技术将使用绘画隐喻开发。 几个世纪以来，艺术家一直使用一种分裂和争议的方法来创作绘画，代表了不同油漆层的场景的不同方面。 此外，艺术家使用刷子的纹理，大小，形状，颜色和不透明度的许多特征来代表画布上场景的重要特征，描绘了场景的本质并消除了不必要的细节。 在显示卷数据的上下文中，这两种技术以及使用它们的集体艺术经验都可以应用于计算机图形。 理解矢量值和张量值数据的技术特别受益，因为卷包含大量信息，并且张量和矢量值具有许多相关的相互依存方面。 现有技术的能力有限，可以有效地抽象数据并同时显示数据的许多相关方面，但是新技术将解决这两个问题。 结果，它们将在洞悉所测得的物理现象以及传达洞察力方面更有效。 由于这些技术将在两个学科中的三个特定问题应用下开发，因此它们可能具有更广泛的应用。