In the registration process a 3D transformation is computed between common parts of two point clouds.

Often it is used to create a 3D surface from a point cloud through either downsampling or upsampling.

If a group of data points forms a cluster, then the geometry of this point cloud can be determined.

A point cloud is a set of data points in some coordinate system.

The point cloud represents the set of points that the device has measured.

There are many techniques for converting a point cloud to a 3D surface.

Geometric dimensions and tolerances can also be extracted directly from the point cloud.

The point clouds are also employed in order to generate 3D model of urban environment, e.g.

Hough transform has also been used to find cylindrical objects in point clouds using a two step approach.

With knowledge of the camera's intrinsic calibration parameters, a range image can be converted into a point cloud.