3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation

Abstract

To address the registration problem in current machine vision, a new three-dimensional (3-D) point cloud registration algorithm that combines fast point feature histograms (FPFH) and greedy projection triangulation is proposed. First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation. Thereafter, the sample consensus initial alignment method is applied for initial transformation to implement initial registration. By adjusting the initial attitude between the two cloud points, the improved initial registration values can be obtained. Finally, the iterative closest point method is used to obtain a precise conversion relationship; thus, accurate registration is completed. Specific registration experiments on simple target objects and complex target objects have been performed. The registration speed increased by 1.1% and the registration accuracy increased by 27.3% to 50% in the experiment on target object. The experimental results show that the accuracy and speed of registration have been improved and the efficient registration of the target object has successfully been performed using the greedy projection triangulation, which significantly improves the efficiency of matching feature points in machine vision.

Geometric Modeling of Rosa roxburghii Fruit Based on Three-Dimensional Point Cloud Reconstruction

“…Reconstruction. Nowadays, some wellknown reconstruction algorithms based on point cloud have been proven to have good reconstruction effects on solid surfaces, such as ball pivoting [27], Poisson reconstruction [28], screened Poisson reconstruction [29], marching cubes [30], alpha shapes [31], greedy projection triangulation [32], and Delaunay triangulation [33]. is paper uses the Poisson reconstruction algorithm, screened Poisson reconstruction algorithm, greedy projection triangulation algorithm, and Delaunay triangulation algorithm to reconstruct the 3D model of Rosa roxburghii fruit.…”

Special Features on Intelligent Imaging and Analysis

“…Another registration task can be found as a point cloud registration for 3D datasets. Liu et al [29] presented a 3D point cloud registration algorithm based on a greedy projection triangulation method to address the 3D problem.…”

Physical Parameter Identification Algorithm Modeling for Complex Microsystem via Triangulation Functions

“…The source area is placed in a super-region filled with the nodes in accordance with a given density of node placement, then the nodes lying near the border of the region are projected onto it, and the nodes outside the region are removed. There are other, more complex methods [12,13,15,16]. A common disadvantage of all methods based on the Delaunay criterion is a high sensitivity to the accuracy of machine calculations.…”