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While point clouds can be directly rendered and inspected, [10] [11] point clouds are often converted to polygon mesh or triangle mesh models, non-uniform rational B-spline (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 ...
An open surface with u- and v-flow lines and Z-contours shown. In technical applications of 3D computer graphics such as computer-aided design and computer-aided manufacturing, surfaces are one way of representing objects. The other ways are wireframe (lines and curves) and solids.
Originally introduced for 2D point cloud map matching in simultaneous localization and mapping (SLAM) and relative position tracking, [1] the algorithm was extended to 3D point clouds [2] and has wide applications in computer vision and robotics. NDT is very fast and accurate, making it suitable for application to large scale data, but it is ...
Point set registration is the process of aligning two point sets. Here, the blue fish is being registered to the red fish. In computer vision, pattern recognition, and robotics, point-set registration, also known as point-cloud registration or scan matching, is the process of finding a spatial transformation (e.g., scaling, rotation and translation) that aligns two point clouds.
This 3D model consists of a polygon mesh or point cloud of geometric samples on the surface of the subject. These points can then be used to extrapolate the shape of the subject (a process called reconstruction). If colour information is collected at each point, then the colours or textures on the surface of the subject can also be determined.
When scanning a 3D point cloud, errors and various deviations can occur, which causes noise in the data. This complicates the estimation of some local point cloud characteristics, such as surface normals. These inaccuracies can lead to significant errors in further processing and it is therefore advisable to remove them with a suitable filter.
Triangulated irregular network TIN overlaid with contour lines. In computer graphics, a triangulated irregular network (TIN) [1] is a representation of a continuous surface consisting entirely of triangular facets (a triangle mesh), used mainly as Discrete Global Grid in primary elevation modeling.
See Ronald Fedkiw's academic web page for many pictures and animations showing how the level-set method can be used to model real-life phenomena. Multivac is a C++ library for front tracking in 2D with level-set methods. James Sethian's web page on level-set method. Stanley Osher's homepage. The Level Set Method. MIT 16.920J / 2.097J / 6.339J.