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Sphere Detection
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This algorithm allows detecting specific spheres in a point cloud

Input
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A single point cloud.


Output
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An annotation representing a sphere.

Description
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The algorithm creates a sphere with a specific radius from a given point cloud. It searches for the sphere in a certain Region of Interest (ROI), which can either be the whole point cloud bounding volume or be determined by a Hough-Transform given the sphere's target radius. Internally it uses a RANSAC approach to find a sphere in the ROI.
Following parameters are available:

* **Inlier threshold**: The distance in world units until which a point in the RANSAC algorithm is considered to be supporting the current hypothesis.
* **Fixed sphere radius**: The radius of the sought-after sphere; set to ``-1`` if not known.
* **Maximal residual error**: The maximum residual of supporting points to RANSAC sphere up to which a result is considered valid.
* **Minimum inliers**: The minimum number of supporting points in RANSAC down to which a result is considered valid.
* **ROI detection mode**: Determines how the ROI is to be determined. Can be either ``None`` (in which case the whole bounding volume is used) or ``Hough Voting``, which performs a Hough-Transform on the point cloud to detect the most likely sphere with the given radius.
* **Max voting volume extent**: The maximum extent of the volume used for Hough-Transform based ROI detection in world units.
* **Point cloud index skip**: The fraction of points to be used for Hough-Transform based ROI detection (determines the increment when iterating through the points, ``1`` means to use all points).
* **Relative ROI margin**: A fraction of the sphere's radius to be added to the ROI detected by Hough-Transform.