Register two point clouds and estimate a rigid transformation.
This samples loads point cloud data from a file and
- creates a transformed version of the input cloud
- smoothes surface with the Moving Least Squares method
- computes surface normals
- computes Fast Point Feature Histogram (FPFH) feature description
- computes Fast Global Registration
- transforms second cloud back to its original position
This sample can be run on the emulator or any device with AppEngine version 2.6.0 or higher and supporting PointClouds.
For more information on fast global registration see: http://vladlen.info/publications/fast-global-registration/
algorithm, point-cloud, sample, sick-appspace