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: 1331009
• 负责人: Carola Wenk
• 金额: $ 6.33万
• 依托单位: Tulane University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1331009&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实践中形状处理的速度，质量和生产率。几何形状是广泛的尖端技术领域的核心，包括计算机视觉，计算机辅助设计（CAD），机器人技术，生物信息学，计算生物学，计算生物学，医学成像，地理信息系统（GIS）和药物设计，在其中进行了多种操纵和处理的研究，以进行众多的研究，以进行良好的研究效率和相关性。 （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沟通，对应用问题的理论性贡献更大，并追求更强的理论基础，这可以成为更广泛的应用范围的基础。具体而言，这项研究涉及多个应用项目，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，以便在具有非常嘈杂的数据的地区为高通量处理铺平道路。理论项目包括曲线和表面的匹配和距离测量问题，多曲线匹配，对地球距离测量的一般研究的启动，其中使用表面上的最短路径测量距离，并简化形状。将研究下限，以便更好地了解问题的结构，并且将设计对应用程序友好的算法，例如输出敏感算法和近似算法，以更好地应对异常值和嘈杂的输入。