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基于强度的地面激光扫描仪三维点云随机模型的确定。

Determination of Intensity-Based Stochastic Models for Terrestrial Laser Scanners Utilising 3D-Point Clouds.

机构信息

Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany.

Photogrammetry & Laser Scanning Lab, HafenCity University Hamburg, 20457 Hamburg, Germany.

出版信息

Sensors (Basel). 2018 Jul 7;18(7):2187. doi: 10.3390/s18072187.

DOI:10.3390/s18072187
PMID:29986495
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6069488/
Abstract

Recent advances in stochastic modelling of reflectorless rangefinders revealed an inherent relationship among raw intensity values and the corresponding precision of observed distances. In order to derive the stochastic properties of a terrestrial laser scanner’s (TLS) rangefinder, distances have to be observed repeatedly. For this, the TLS of interest has to be operated in the so-called 1D-mode—a functionality which is offered only by a few manufacturers due to laser safety regulations. The article at hand proposes two methodologies to compute intensity-based stochastic models based on capturing geometric primitives in form of planar shapes utilising 3D-point clouds. At first the procedures are applied to a phase-based Zoller + Fröhlich IMAGER 5006h. The generated results are then evaluated by comparing the outcome to the parameters of a stochastic model which has been derived by means of measurements captured in 1D-mode. Another open research question is if intensity-based stochastic models are applicable for other rangefinder types. Therefore, one of the suggested procedures is applied to a Riegl VZ-400i impulse scanner, as well as a Leica ScanStation P40 TLS that deploys a hybrid rangefinder technology. The generated results successfully demonstrate alternative methods for the computation of intensity-based stochastic models as well as their transferability to other rangefinder technologies.

摘要

最近在无反射测距仪的随机建模方面的进展揭示了原始强度值与观测距离的相应精度之间存在内在关系。为了推导出地面激光扫描仪(TLS)测距仪的随机特性,必须重复观测距离。为此,需要以所谓的 1D 模式操作感兴趣的 TLS,由于激光安全法规,只有少数制造商提供此功能。本文提出了两种基于强度的方法来计算基于捕捉三维点云中的平面形状的几何基元的随机模型。首先,将这些过程应用于基于相位的 Zoller + Fröhlich IMAGER 5006h。生成的结果通过将结果与通过 1D 模式捕获的测量得出的随机模型的参数进行比较来评估。另一个开放的研究问题是强度为基础的随机模型是否适用于其他测距仪类型。因此,建议的程序之一应用于 Riegl VZ-400i 脉冲扫描仪,以及采用混合测距仪技术的 Leica ScanStation P40 TLS。生成的结果成功地证明了用于计算基于强度的随机模型的替代方法及其在其他测距仪技术中的可转移性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/df12cdd5b7fe/sensors-18-02187-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/cb179333c13b/sensors-18-02187-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/f9499d7a94b2/sensors-18-02187-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/28aa5bee3c51/sensors-18-02187-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/f3ceb2bfdf58/sensors-18-02187-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/1b533a515154/sensors-18-02187-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/cfbd80f99167/sensors-18-02187-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/b67e3116bddf/sensors-18-02187-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/92c191d71538/sensors-18-02187-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/377e558b180f/sensors-18-02187-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/77d7c230e204/sensors-18-02187-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/9a8755f421a5/sensors-18-02187-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/9f2547b59fe4/sensors-18-02187-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/df12cdd5b7fe/sensors-18-02187-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/cb179333c13b/sensors-18-02187-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/f9499d7a94b2/sensors-18-02187-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/28aa5bee3c51/sensors-18-02187-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/f3ceb2bfdf58/sensors-18-02187-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/1b533a515154/sensors-18-02187-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/cfbd80f99167/sensors-18-02187-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/b67e3116bddf/sensors-18-02187-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/92c191d71538/sensors-18-02187-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/377e558b180f/sensors-18-02187-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/77d7c230e204/sensors-18-02187-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/9a8755f421a5/sensors-18-02187-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/9f2547b59fe4/sensors-18-02187-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/030a/6069488/df12cdd5b7fe/sensors-18-02187-g013.jpg

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