Point cloud (laser scanner)
Introduction
A point cloud is a set of vertices in a three-dimensional coordinate system. These vertices are commonly identified as X, Y, and Z coordinates and are representations of the external surface of an object.
Point clouds are usually created with a three-dimensional laser scanner. This instrument automatically measures a large number of points on the surface of an object, and generates a data file with a cloud of points. The point cloud represents the set of points that the device has measured.
Point clouds have multiple applications, including three-dimensional CAD modeling of manufactured parts, quality inspection in metrology, and many others in visualization, animation, texturing, and mass customization applications.
Although point clouds can be reviewed and textured directly,[1] they are not typically used in this way in most 3D applications, as they are converted into polygonal mesh models or irregular triangular meshes, NURBS surface models, or CAD models through a process called surface reconstruction.
There are several techniques to convert a point cloud into a three-dimensional surface. Some procedures such as Delaunay triangulation or alpha shapes construct a network of triangles from the vertices of the point cloud, while others convert the point cloud into a voxel volume and reconstruct the implicit surface using a marching cubes algorithm").[2].
One application where point clouds are used directly is metrology and industrial inspection. The cloud of a manufactured part is aligned to a CAD model (or other point cloud) and compared to verify differences. These are displayed as color maps that provide a visual indicator of the deviation between the manufactured part and the CAD model. Geometric dimensions and tolerances can also be extracted directly from the point cloud.
Point clouds can also be used to represent volumetric data such as in medical imaging. It is achieved using multi-sampling point clouds and data compression.[3].
In Geographic Information Systems, point clouds are one of the data sources to build digital terrain models.[4].
References
- [1] ↑ Rusinkiewicz, S. and Levoy, M. 2000. QSplat: a multiresolution point rendering system for large meshes. In Siggraph 2000. ACM , New York, NY, 343-352. DOI= http://doi.acm.org/10.1145/344779.344940.: http://doi.acm.org/10.1145/344779.344940
- [2] ↑ Meshing Point Clouds A short tutorial on how to build surfaces from point clouds.: http://meshlabstuff.blogspot.com/2009/09/meshing-point-clouds.html
- [3] ↑ Sitek et al. "Tomographic Reconstruction Using an Adaptive Tetrahedral Mesh Defined by a Point Cloud" IEEE Trans. Med. Imag. 25 1172 (2006).
- [4] ↑ From Point Cloud to Grid DEM: A Scalable Approach.: http://terrain.cs.duke.edu/pubs/lidar_interpolation.pdf