CAREER: Application and Theory of Geometric Shape Handling

职业：几何形状处理的应用和理论

• 批准号: 0643597
• 负责人: Carola Wenk
• 金额: $ 40.05万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643597&HistoricalAwards=false
• 关键词: CAREER; Application; Theory; Geometric; Shape

The objective of this research is to help increase speed, quality, and productivity of shape handling in practice. Geometric shapes are at the core of a wide range of cutting-edge technological sectors including computer vision, computer aided design (CAD), robotics, bioinformatics, computational biology, medical imaging, geographical information systems (GIS), and drug design, in which a multitude of tasks for manipulating and handling geometric shapes have to be performed efficiently and reliably.This research is based on two research tracks: (i) shape handling applications and (ii) shape handling theory. The investigator will continue to foster interdisciplinary communication, contribute more theoretical soundness to applied problems, and pursue a stronger theoretical foundation which can be the basis for a wider range of applications. Specifically, this research involves several applied projects including, but not limited to, computational proteomics, computational neuroscience, and spatiotemporal traffic databases. Semi-automatic algorithms will be combined with theoretical expertise in order to pave the road for high-throughput processing in areas with very noisy data. Theoretical projects include matching and distance measure problems for curves and surfaces, multi-curve matching, initiation of a general study of geodesic distance measures in which distances are measured using shortest paths on a surface, and shape simplification. Lower bounds will be investigated in order to gain better insight into the structure of the problems, and application-friendly algorithms such as output-sensitive algorithms and approximation algorithms will be devised in order to better cope with outliers and noisy inputs.

这项研究的目的是帮助提高速度，质量和生产率的形状处理在实践中。几何形状是计算机视觉、计算机辅助设计（CAD）、机器人技术、生物信息学、计算生物学、医学成像、地理信息系统（GIS）和药物设计等一系列尖端技术领域的核心，在这些领域中，必须高效、可靠地执行大量操作和处理几何形状的任务。（i）形状处理应用和（ii）形状处理理论。研究人员将继续促进跨学科的交流，为应用问题提供更多的理论合理性，并追求更强大的理论基础，这可以成为更广泛应用的基础。具体而言，这项研究涉及几个应用项目，包括但不限于，计算蛋白质组学，计算神经科学和时空交通数据库。半自动算法将与理论专业知识相结合，以便为具有非常嘈杂数据的区域的高通量处理铺平道路。理论项目包括匹配和距离测量问题的曲线和曲面，多曲线匹配，启动一般研究的测地距离措施，其中距离测量使用最短路径的表面上，形状简化。将研究下限，以便更好地了解问题的结构，并设计应用友好的算法，如输出敏感算法和近似算法，以便更好地科普离群值和噪声输入。