Color Point Cloud Registration Based on Supervoxel Correspondence

IEEE Access

Yang Yang¹  Dexing Zhong²  Shaoyi Du³  Weile Chen³  Muyi Wang⁴ 

[1] School of Electronic and Information Engineering, Xi&x2019;School of Software Engineering, Xi&x2019;an Jiaotong University, Xi&x2019;an, China;

关键词: Color point cloud registration;    hybrid feature;    mutual correspondence matching;   

DOI  :  10.1109/ACCESS.2020.2963987

来源: DOAJ

【 摘 要 】

With the development of RGBD sensors, the high-quality color point cloud can be obtained expediently. In this paper, we propose a novel registration method for 3D color point clouds from different views, which is a critical issue in many applications. Different from traditional feature-based methods, we design a hybrid feature representation with color moments of the point, which could be applied naturally for any color point cloud. And these features are extracted from point clouds based on the supervoxel segmentation. By jointly conducting these features for similarity measure, a weight parameter is dynamically adapted between the color and the spatial information. The registration algorithm is under a classic iterative framework for building the correspondence and estimating transformation parameters. In addition, we provide a mutual correspondence matching condition with hybrid features to build some more robust relationships for estimating transformation parameters. Experimental results demonstrate that our method can effectively reduce the number of point data for registration and achieve good matching results even in a poor initial condition.

【 授权许可】

Unknown