For quite some time, I’ve been saying to my peers and detractors that 2018 might finally be the year the “cloud” takes off, whether we’re talking storage in the cloud, CAD in the cloud, simulation in the cloud – whatever in the cloud. I also think that another “cloud” innovation that will get its just attention is the point cloud that will grow far beyond its traditional role for representing surfaces to becoming an integral component of 3D modeling and maybe even virtual reality.
So, exactly what is a point cloud? Technically, a point cloud is a data base containing points in a 3D coordinate system. A point cloud is a very accurate digital record of an object or space. It is saved as a (very) large number of points that cover surfaces of a scanned/sensed object. The points in a point clouds are always located on the external surfaces of visible objects, because they are the points reflected from scanned objects.
In a three-dimensional coordinate system, these points are usually defined by X, Y, and Z coordinates, and intended to represent the external surface of an object.
Point clouds can be created by several methods, including 3D scanners and photographs. These devices measure a large number of points on an object’s surface, and often output a point cloud as a data file. The point cloud represents the set of points that the device has measured.
Reality Capture – Converting Photos Into 3D Models
The key factor in acquiring point cloud data is the access/visibility to scanned surfaces. It is important to remember, that point clouds are created with visible access to real objects. Regardless of the method of acquisition (scanner or photos). It is impossible to obtain points on the surfaces that are not visible from the position from which data is collected. This means that to cover entire objects, many scanning positions must be combined.