The recent development of high-precision subsea optical scanners allows for 3D keypoint detectors and feature descriptors to be leveraged on point cloud scans from subsea environments. However, the literature lacks a comprehensive survey to identify the best combination of detectors and descriptors to be used in these challenging and novel environments. This paper aims to identify the best detector/descriptor pair using a challenging field dataset collected using a commercial underwater laser scanner. Furthermore, studies have shown that incorporating texture information to extend geometric features adds robustness to feature matching on synthetic datasets. This paper also proposes a novel method of fusing images with underwater laser scans to produce coloured point clouds, which are used to study the effectiveness of 6D point cloud descriptors.
翻译:最近开发的高精度海底光学扫描仪使3D关键点探测器和特征描述器能够用于海底环境中的点云扫描,然而,文献缺乏一项全面调查,以确定在这些具有挑战性和新颖环境中使用的探测器和描述器的最佳组合,本文件的目的是利用利用利用商业水下激光扫描仪收集的具有挑战性的实地数据集,确定最佳探测器/描述仪。此外,研究还表明,将纹理信息纳入扩展几何特征,增加了合成数据集特征匹配的强度。本文还提出了一种新型方法,即用水下激光扫描法对图像进行引信,以生成有色点云,用于研究6D点云描述器的有效性。