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Concept
Point-set registration
Résumé
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. The purpose of finding such a transformation includes merging multiple data sets into a globally consistent model (or coordinate frame), and mapping a new measurement to a known data set to identify features or to estimate its pose. Raw 3D point cloud data are typically obtained from Lidars and RGB-D cameras. 3D point clouds can also be generated from computer vision algorithms such as triangulation, bundle adjustment, and more recently, monocular image depth estimation using deep learning. For 2D point set registration used in image processing and feature-based , a point set may be 2D pixel coordinates obtained by feature extraction from an image, for example corner detection. Point cloud registration has extensive applications in autonomous driving, motion estimation and 3D reconstruction, object detection and pose estimation, robotic manipulation, simultaneous localization and mapping (SLAM), , virtual and augmented reality, and medical imaging.
As a special case, registration of two point sets that only differ by a 3D rotation (i.e., there is no scaling and translation), is called the Wahba Problem and also related to the orthogonal procrustes problem.
The problem may be summarized as follows:
Let be two finite size point sets in a finite-dimensional real vector space , which contain and points respectively (e.g., recovers the typical case of when and are 3D point sets). The problem is to find a transformation to be applied to the moving "model" point set such that the difference (typically defined in the sense of point-wise Euclidean distance) between and the static "scene" set is minimized. In other words, a mapping from to is desired which yields the best alignment between the transformed "model" set and the "scene" set.
Source officielle
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