CARGO: Shape Analysis From Point Cloud Data

DMS-0138456 Leonidas J.Guibas3-D形状获取的扫描技术的广泛可用性导致了学术界和工业界用于从扫描仪返回的原始数据建立表面网格的算法和软件的开发。对于大多数光学和接触式传感器，这些原始数据是无组织的点云或PCD集(点云数据)的形式；目前的扫描仪能够生成亚毫米精度的物体表面采样。在如此高的分辨率下，这些密集的PCD集本身就成为对象几何体的适当表示，而不需要拟合网格或曲面。根据这笔赠款开展的工作将利用代数拓扑学和计算几何学的工具，对PCD数据进行直接和有效的局部和全局分析。具体地说，将开发和分析用于PCD特征检测、分割、匹配、拟合和压缩的算法。预计PCD集不仅在重建或可视化应用中将成为对象几何的轻量级和方便的表示，而且在用于机器人探索或产品定制等应用的以PCD格式直接查询对象几何的大部分未被探索的领域中更是如此。在接下来的五年里，我们预计将看到3D扫描的广泛商业部署，以及紧凑型、便携式扫描设备的出现。通过利用获得的PCD数据，将有可能为用户定制和定制制造的产品，达到到目前为止还不可能达到的程度。根据这项提议开发的技术应该会促进服装、鞋类、助听器、正畸、假肢和汽车行业的这一转变。

DMS-0138456Leonidas J. GuibasThe wide availability of scanning technologies for 3-d shape acquisition has led to the development of algorithms and software, in both academia and industry, for building surface meshes from the raw data returned by the scanner. For most optical and contact sensorsthis raw data is in the form of an unorganized point cloud, or PCD set (point cloud data); current scanners are able to generate object surface samplings at submillimeter accuracy. At such high resolutions,these dense PCD sets become adequate representations of object geometry in themselves, without any need to fit a mesh or surface. The work undertaken under this grant will exploit tools from algebraic topology and computational geometry to perform local and globalanalysis directly and efficiently on PCD data. Specifically,algorithms for PCD feature detection, segmentation, matching, fitting, and compression will be developed and analyzed.It is expected that PCD sets will become a lightweight and convenient representation of object geometry not only in reconstruction or visualization applications, but even more so in the largely unexplored area of directly interrogating object geometry in the PCD format forapplications such as robotic exploration or productcustomization. Over the next five years we can expect to see wide commercial deployment of 3-d scanning and the appearance of compact, portable scanning devices. By exploiting the acquired PCD data it will become possible to customize and tailor manufactured products to their user to a degree that has been impossible up to now. Technology developed under this proposal should facilitate this transition in the apparel, footwear, hearing-aid, orthodontic, prosthetics, and automotive industries.