The Z-axis, X-axis, Weight and Disambiguation Methods for Constructing Local Reference Frame in 3D Registration: An Evaluation
Bao Zhao, Xianyong Fang, Jiahui Yue, Xiaobo Chen, Xinyi Le, Chanjuan, Zhao

TL;DR
This paper systematically evaluates various methods for constructing local reference frames in 3D registration, analyzing their merits and demerits across multiple datasets, and proposes improved axes with better performance.
Contribution
It provides a comprehensive analysis of z-axis, x-axis, weight, and disambiguation methods in LRF construction, including new axes with superior performance.
Findings
Certain new LRF axes outperform state-of-the-art methods.
Evaluation across six datasets reveals strengths and weaknesses of different methods.
Analysis guides better selection of LRF methods for 3D registration.
Abstract
The local reference frame (LRF), as an independent coordinate system generated on a local 3D surface, is widely used in 3D local feature descriptor construction and 3D transformation estimation which are two key steps in the local method-based surface matching. There are numerous LRF methods have been proposed in literatures. In these methods, the x- and z-axis are commonly generated by different methods or strategies, and some x-axis methods are implemented on the basis of a z-axis being given. In addition, the weight and disambiguation methods are commonly used in these LRF methods. In existing evaluations of LRF, each LRF method is evaluated with a complete form. However, the merits and demerits of the z-axis, x-axis, weight and disambiguation methods in LRF construction are unclear. In this paper, we comprehensively analyze the z-axis, x-axis, weight and disambiguation methods in…
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Taxonomy
Topics3D Shape Modeling and Analysis · Image Processing and 3D Reconstruction · Robotics and Sensor-Based Localization
