General Visible Surface Reconstruction Based on Growing Three Dimensional Curves and Surfaces

这是为期三年的持续奖励的第一年资助。从复杂场景中获取的三维数据对可见曲面重建技术的健壮性和通用性提出了强烈的要求。在这项研究中，将开发一种完整的重建算法，基于扩展的三维图像邻域中点分布的不对称性来区分曲面、空间曲线和点云。该算法的性能将在合成数据和从各种传感器获取的距离数据上进行解析研究和实验验证。该软件将提供给其他研究人员进行进一步测试。目标是充分了解这项技术的优点和缺点。这将为未来的研究提供坚实的基础，并使评估该技术在特定应用中的有用性变得容易。潜在的应用范围从机器人导航到逆向工程。

This is the first-year funding of a three-year continuing award. Three-dimensional data taken from complex scenes place strong demands on the robustness and generality of visible surface reconstruction techniques. In this research a complete reconstruction algorithm will be developed that distinguishes between surfaces, space curves, and clouds of points based on asymmetries in point distributions in expanding three-dimensional image neighborhoods. The properties of this algorithm will be studied analytically and confirmed experimentally on both synthetic data and range data acquired from a variety of sensors. The software will be made available to other researchers for further testing. The goal is to understand fully both the strengths and weaknesses of the technique. This will provide a solid basis for future research and will make it easy to evaluate the technique's usefulness for specific applications. Potential applications range from robotic navigation to reverse engineering.