From Existing Clouds Uniform Spacing
This command builds a new cloud from the selected clouds with a reduced number of cloud points. It returns an approximately uniform distribution of cloud points keeping only the closest cloud points at the desired point distance specified.
Cloud Filtering and Sub-Sampling
Many functions within SA provide access to an additional layer of thinning either as part of the association or evaluation process. This thinning of the input cloud can greatly increase processing speeds by reducing the size of the resulting cloud. The standard cloud thinning controls include the following options
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No Thinning (Use All Points). Selecting None will disable input cloud thinning.
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Random Thin. A random selection of points will be taken from the point input cloud until the Desired Count is reached. This method ensures an unbiased selection of cloud points for use. A random selection will pick different points each time it is run but ensures the same number of cloud points are returned.
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Every N-th Point. Provides either of two filter methods. If the Maximum Point Count is set to 0 it provides a simple decimation strategy where it will return 1 cloud point for every Skip Interval. When used together with a Max Point Count, the Skip Interval is effectively expanded to equal the Input count divided by the Max Point Count, ensuring no more than the Max Point Count will be returned.
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Use Spatial Filtering. This filtering mode uses a moving filter window to walk through the data evaluating points within the specified 3D volume or Voxel Size. It attempts to return the most representable cloud point from the available data within that region by retaining the point closest to the average. The Minimum Points Per Voxel control provides a means to exclude regions of low density as part of the sub-sampling process. This can be helpful in excluding outliers.