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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 ...
Point cloud library is widely used in many different fields, here are some examples: stitching 3D point clouds together; recognize 3D objects on their geometric appearance; filtering and smoothing out noisy data; create surfaces from point clouds; aligning a previously captured model of an object to some newly captured data
3. Point cloud cleaning and decimation Regardless of the methodology of the data acquisition, the resulting point cloud is usually filtered and cleaned from unwanted objects, e.g. vegetation. Decrease of the overall point cloud density might be required depending on the outcrop surface complexity and size of the dataset. 4.
CloudCompare an open source point and model processing tool that includes an implementation of the ICP algorithm. Released under the GNU General Public License. PCL (Point Cloud Library) is an open-source framework for n-dimensional point clouds and 3D geometry processing. It includes several variants of the ICP algorithm.
CloudCompare is a 3D point cloud processing software (such as those obtained with a laser scanner).It can also handle triangular meshes and calibrated images. Originally created during a collaboration between Telecom ParisTech and the R&D division of EDF, the CloudCompare project began in 2003 with the PhD of Daniel Girardeau-Montaut on Change detection on 3D geometric data. [2]
Point clouds are also sometimes used as temporary ways to represent an object, with the goal of using the points to create one or more of the three permanent representations. Open and closed surfaces [ edit ]
Modern computed axial tomography and magnetic resonance imaging scanners can be used to create solid models of internal body features called voxel-based models, with images generated using volume rendering. Optical 3D scanners can be used to create point clouds or polygon mesh models of external body features. Uses of medical solid modeling;
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.