What Is a Point Cloud?

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  • Written By: Sandi Johnson
  • Edited By: John Allen
  • Last Modified Date: 11 October 2019
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Computer modeling and computerized three dimensional graphics rely on a series of points along the surface for proper renderings. Multidimensional points provide computers the information necessary to recreate a physical object in a digital three dimensional plane. The points associated with a particular model, image, or other graphic are defined by X, Y, and Z coordinates. All the coordinates relating to such an image are included in a concept called a point cloud. Point clouds represent all the coordinates that help illustrate the external surface of a three dimensional object.

Industries such as manufacturing use a point cloud for reverse engineering, quality assurance, customization, and product design. Using computer-aided design (CAD) models, a particular part can be scanned and analyzed for accuracy and standardization. A finished part, when scanned and converted to a series of coordinates, should match CAD models when the renderings are overlaid. In medical manufacturing, the use of similar 3D modeling can assist with the customization of medical devices to meet the needs of specific patients. Medical imaging, such as 3D computerized axial tomography (CAT) scans, also use such data compression techniques to convert and compile images into a three or four dimensional computer model.


Alone, a point cloud will not render a computerized reconstruction of an object. Instead, point clouds are used to create a model using a variety of surface reconstruction methods. For example, a triangle mesh model connects vertices using a series of triangles to render a rough outline of an object's surface. CAD and non-uniform rational basis spline (NURBS) surface models are also commonly associated with various applications and surface reconstruction methodologies.

Three dimensional renderings are not the only use for a point cloud. When rendering the surface of an object, the addition of color or texture information results in a four dimensional point cloud. Such additional information allows users more agility in terms of working with reconstructed images and object surfaces. Images that use a point cloud with color information allow data processing software to reconstruct a more true-to-life computer model.

Collecting scans to convert into a point cloud requires specialized equipment in order to provide the detailed information needed for reconstruction. Special 3D cameras, laser scanners, and other devices are needed, as well as some form of processing framework to interpret and render point cloud data. Certain computer programs can render point cloud models based on synthetically input variables. Synthetic point cloud processing further expands computerized modeling options for manufacturing, medical devices, computer generated graphics for film, and virtual world or virtual environment creation.


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