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System and method providing a scalable and efficient space filling curve approach to point cloud feature generation

机译:提供用于点云特征生成的可扩展且有效的空间填充曲线方法的系统和方法

摘要

Systems, methods, and other embodiments are disclosed for identifying features within point cloud data. In one embodiment, point cloud data is read which represents multiple points of at least one point cloud in a multi-dimensional space. Each point in the point cloud data is defined by an attribute value quantifying an attribute of the point and a set of coordinates specifying a location of the point in the multi-dimensional space. The set of coordinates for each point is transformed into a space-filling distance value representing a distance along a space-filling curve. The points are sorted according to the space-filling distance values to generate a sorted order of the points. The points are traversed in the sorted order and output data points are derived, while traversing the points, based on a specified feature criterion. The output data points identify a feature within the at least one point cloud.
机译:公开了用于识别点云数据内的特征的系统,方法和其他实施例。在一实施例中,读取代表多维空间中至少一个点云的多个点的点云数据。点云数据中的每个点由量化该点的属性的属性值和指定该点在多维空间中的位置的一组坐标定义。每个点的坐标集被转换为代表沿着空间填充曲线的距离的空间填充距离值。根据空间填充距离值对这些点进行排序,以生成这些点的排序顺序。按照指定的顺序遍历这些点,并在遍历这些点的基础上,根据指定的特征标准得出输出数据点。输出数据点标识至少一个点云中的要素。

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