Registration is an essential process in dealing with point clouds obtained from multiple scans of the same object by aligning the data sets to each other. Polygonica allows this to be done semi-automatically using user guidance, and by a completely automatic process of nearly aligned sets.
Filtering automatically removed unwanted outliers, a common issue with scanned data.
Sampling can be used to reduce the size of point clouds by eliminating points in over-sampled regions. This enables Polygonica to handle point clouds consisting of tens of millions of points.
Polygonica smoothing can be applied directly to point clouds to remove noise - which is common in scanned data sets.
Polygonica can create a mesh from all or part of a point cloud, in other words, Polygonica can do meshing. The resulting solid mesh can be used in many of Polygonica’s mesh processing algorithms giving users greater flexibility and option to apply further Polygonica processing.
A hole-filling algorithm has been added specifically to identify and reconstruct data from low quality scans using feature recognition on noisy scan meshes.
The tools provided by Polygonica are extremely flexible, can be applied to all or part of a point cloud, and in almost any sequence. The possibilities are endless for users to operate on the whole point cloud or to select parts of the point cloud on which operations can then be specifically applied.
