Postdoctoral: Sampling Based Geometric Modeling

博士后：基于采样的几何建模

• 批准号: 0102280
• 负责人: Tamal Dey
• 金额: $ 6.6万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2003-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0102280&HistoricalAwards=false
• 关键词: Postdoctoral; Sampling; Based; Geometric; Modeling

EIA-0102280Dey, Tamal K.Ohio State UniversityCISE Postdoctoral Associates in Experimental Computer Science: Sampling Based Geometric ModelingMany application domains ranging from engineering to medicine require the computer modeling of physical objects. Laser range scanners and other modern scanning devices are capable of sampling large numbers of points on the surface of a physical object. Computing a model of an object, often referred to as surface reconstruction, has received wide attention in recent years. In the proposed postdoctoral training and research project, the problem of how to perform surface reconstruction of a physical object from a set of sampled points will be further studied. Specifically, a postdoctoral associate will focus on extending the cocone algorithm to handle large, noisy, and undersampled sets of data points. The associate's research will contribute to building a software library that provides the reconstruction functionality needed to meet the widespread demands of a range of users across disciplines.

EIA-0102280 Dey，Tamal K.俄亥俄州州立大学CISE实验计算机科学博士后研究员：基于采样的几何建模从工程到医学的许多应用领域都需要物理对象的计算机建模。激光测距扫描仪和其他现代扫描设备能够对物理对象表面上的大量点进行采样。计算物体的模型，通常被称为表面重建，近年来受到广泛关注。在拟议的博士后培训和研究项目中，将进一步研究如何从一组采样点进行物理对象的表面重建的问题。具体来说，博士后助理将专注于扩展cocone算法，以处理大型，噪声和欠采样的数据点集。 该助理的研究将有助于建立一个软件库，提供满足跨学科用户广泛需求所需的重建功能。