A point cloud is a set of data points in space. It is a collection of data points defined by a given coordinates system. In a 3D coordinates system, a point cloud may define the shape of some real or created physical system. Point clouds are used to create 3D meshes and other models used in 3D modeling. Point clouds are generally produced by 3D scanners which measure many points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering, and mass customization applications.

Point clouds are often aligned with 3D models or with other point clouds, a process known as point set registration. For industrial metrology or inspection using industrial computed tomography, the point cloud of a manufactured part can be aligned to an existing model and compared to check for differences. Geometric dimensions and tolerances can also be extracted directly from the point cloud. While point clouds can be directly rendered and inspected, point clouds are often converted to polygon mesh or triangle mesh models, NURBS surface models, or CAD models through a process commonly referred to as surface reconstruction.

There are many techniques for converting a point cloud to a 3D surface.  Some approaches, like Delaunay triangulation, alpha shapes, and ball pivoting, build a network of triangles over the existing vertices of the point cloud, while other approaches convert the point cloud into a volumetric distance field and reconstruct the implicit surface so defined through a marching cubes algorithm. Developing digital twins of assets from LiDAR point clouds is one of the most significant applications of point clouds.