CAREER: Reconstructing Geometrically and Topologically Correct Models

职业：重建几何和拓扑正确的模型

基本信息

批准号：
0846072
负责人：
Tao Ju
金额：
$ 47.66万
依托单位：
Washington University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-01 至 2015-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0846072&HistoricalAwards=false
关键词：
CAREER Reconstructing Geometrically Topologically Correct

项目摘要

Abstract:PI: Ju, Tao (0846072)CAREER: Reconstructing Geometrically and Topologically Correct ModelsBio-medical imaging and 3D scanning are widely used for acquiring realistic digital models of real-world objects, from those that are around us, like coffee mugs and statues, to those within us, like proteins and organs. In many applications, polygonal surfaces need to be reconstructed from the data captured by scanning or imaging. Besides visualization, these polygonal models have wide uses in computation and manufacturing, where geometrically and topologically correct models are required. However, as the input data is often noisy or incomplete, it is still difficult in practice to obtain correct polygonal surfaces using existing reconstruction algorithms. The reconstructed surface may exhibit geometric inconsistencies including gaps, holes and intersections, and more often, topological artifacts such as handles and disconnections. Furthermore, most reconstruction algorithms that promise geometrically correct outputs are designed for closed surfaces with well-defined inside and outside, and hence not applicable to surfaces that contain intended open boundaries or interior membranes. These more general surfaces are commonly used in CAD as well as bio-medical modeling.This research is developing robust polygonal surface reconstruction algorithms that offer guarantees for geometric and topological correctness. To achieve this goal, an integrated framework is developed that combines and extends existing surface reconstruction and model repair algorithms to produce correct polygonal models that best represent the input data, in the form of either 3D point clouds or grayscale volumes. The research is also exploring new reconstruction and repair algorithms for open and non-manifold surfaces, thereby extending the correctness guarantees to a much larger class of models than those can be handled by existing methods.

摘要：PI：鞠涛 (0846072) 职业：重建几何和拓扑正确的模型生物医学成像和 3D 扫描广泛用于从我们周围的物体（例如咖啡杯和雕像）获取现实世界物体的真实数字模型，对于我们体内的那些，比如蛋白质和器官。在许多应用中，需要根据扫描或成像捕获的数据重建多边形表面。除了可视化之外，这些多边形模型在需要几何和拓扑正确的模型的计算和制造中也有广泛的用途。然而，由于输入数据通常是有噪声或不完整的，在实践中使用现有的重建算法仍然很难获得正确的多边形表面。重建的表面可能会表现出几何不一致，包括间隙、孔洞和交叉点，更常见的是拓扑伪影，例如手柄和断开连接。此外，大多数承诺几何正确输出的重建算法都是针对具有明确内部和外部的封闭表面而设计的，因此不适用于包含预期开放边界或内部膜的表面。这些更通用的曲面通常用于 CAD 以及生物医学建模。本研究正在开发强大的多边形曲面重建算法，为几何和拓扑的正确性提供保证。为了实现这一目标，开发了一个集成框架，该框架结合并扩展了现有的表面重建和模型修复算法，以生成最能以 3D 点云或灰度体的形式表示输入数据的正确多边形模型。该研究还在探索用于开放和非流形表面的新重建和修复算法，从而将正确性保证扩展到比现有方法可以处理的模型大得多的模型类别。