Multi-view point cloud global optimal registration method based on hierarchical closed-loop constraints

Abstract

The invention discloses a multi-view point cloud global optimization registration method based on hierarchical closed-loop constraints, which belongs to the intersection field of computer vision and laser scanning data processing. The present invention aims at the spatial difference of the registration primitive neighborhood information generated by different scanning angles of the hand, and analyzes the connectivity of the point cloud according to the feature consistency and geometric consistency of the registration primitive, constructs a connectivity graph for the multi-viewpoint cloud, and converts the The similarity transformation between point clouds is unified to the reference coordinate system. Based on the hierarchical closed-loop constraints, through the error analysis and correction of the least squares joint adjustment, the global optimal fine registration result is obtained.

Description

technical field

[0001] The invention belongs to the intersection field of computer vision and laser scanning data processing, and particularly relates to point cloud data preprocessing, multi-view point cloud registration, and automatic research on laser point cloud measurement data processing. Background technique

[0002] Laser scanning measurement technology is an important means to obtain three-dimensional target spatial information. It uses the principle of laser ranging to create a point cloud on the geometric surface of the measured target. Reconstruct the 3D entity of the measured target and various model primitive data such as line, surface and volume. With the development and promotion of 3D point cloud acquisition technology, users can quickly acquire multi-resolution, multi-scale, and multi-temporal point cloud data of scene objects. Among them, the handheld laser scanner has good portability, high geometric accuracy (sub-millimeter level), and can quickly compl...

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