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I am working with structured 2.5D and unstructured 3D data, which generally is available in (X,Y,Z) coordinates, i.e. point clouds. Now I want to impose a regular voxel grid onto the data. This is not meant for visualization purposes, but rather for "cleaning" or fusing the data. I imagine cases, where e.g. 3 points fall within the volume of one voxel. Then I would aim at either just setting this voxel to "activated" and discarding the 3 original points or alternatively I would like to calculate the euclidian mean of the points and return the thus "cleaned" point cloud as an irregularly structured one again.

I hope I could make my intentions clear enough: It's not about visualization and not necessarily about using volumetric cubes instead of points. It's only about manipulating possibily irregular point clouds in a structured way.

I was thinking about kd-tree or octree based solutions in this context, but can anybody point me in the proper direction? Hinting at existing MATLAB implementations would be most appreciated.

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如果数据是不规则间隔的,那么您要使用的是平滑和插值数据点的东西。一个非常好的方法是高斯过程回归。这是相同问题的示例,但在 2D 中

于 2014-01-25T23:40:39.087 回答