基于机器学习的点云配准的强大对应选择方法

IF 1 4区 地球科学 Q4 GEOGRAPHY, PHYSICAL
Wuyong Tao, Dong Xu, Xijiang Chen, Ge Tan
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引用次数: 0

摘要

对应选择是点云配准中不可缺少的过程。点云配准的成功与否很大程度上取决于良好的对应选择方法。为此,本文提出了一种新的通信选择方法。首先,使用两个几何约束(本文提出了其中一个约束)来计算两个对应之间的兼容分数。然后,根据对应关系与其他对应关系的兼容性分数构造对应关系的特征向量。训练支持向量机分类器,利用特征向量对正确和错误的对应进行分类。实验结果表明,我们的方法可以很好地选择正确的对应,并获得较高的精度和f分性能。此外,与其他方法相比,我们的方法对噪声、点密度变化和部分重叠具有最好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Powerful Correspondence Selection Method for Point Cloud Registration Based on Machine Learning
Correspondence selection is an indispensable process in point cloud registration. The success of point cloud registration largely depends on a good correspondence selection method. For this purpose, a novel correspondence selection method is proposed in this paper. First, two geometric constraints, one of which is proposed in this paper, are used to compute the compatibility score between two correspondences. Then, the feature vectors of the correspondences are constructed according to the compatibility scores between the correspondence and others. A support vector machine classifier is trained to classify the correct and incorrect correspondences by using the feature vectors. The experimental results demonstrate that our method can choose the right correspondences well and get high precision and F-score performance. Also, our method has the best robustness to noise, pointdensity variation, and partial overlap compared to the other methods.
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来源期刊
Photogrammetric Engineering and Remote Sensing
Photogrammetric Engineering and Remote Sensing 地学-成像科学与照相技术
CiteScore
1.70
自引率
15.40%
发文量
89
审稿时长
9 months
期刊介绍: Photogrammetric Engineering & Remote Sensing commonly referred to as PE&RS, is the official journal of imaging and geospatial information science and technology. Included in the journal on a regular basis are highlight articles such as the popular columns “Grids & Datums” and “Mapping Matters” and peer reviewed technical papers. We publish thousands of documents, reports, codes, and informational articles in and about the industries relating to Geospatial Sciences, Remote Sensing, Photogrammetry and other imaging sciences.
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