A generic point error model for TLS derived point clouds

Özendi, Mustafa; Akça, Devrim; Topan, Hüseyin

doi:10.1117/12.2269373

Cited by 12 publications

(19 citation statements)

References 11 publications

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“…It was shown that the impact of interest increases for rising incidence angles. Interestingly, a stringent explanatory pattern can still be found in current research, see, e.g., Ozendi et al (2017) and Bolkas & Martinez (2018), that assign various influences into certain categories. In summary, the most relevant influences can be tributed to the survey configuration as well as the local radiometric characteristics of the object.…”

Section: Lidar Intensity As a Quality Measurementioning

confidence: 90%

Methods From Information Extraction From Lidar Intensity Data and Multispectral Lidar Technology

Scaioni

Höfle

Kersting

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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LiDAR is a consolidated technology for topographic mapping and 3D reconstruction, which is implemented in several platforms On the other hand, the exploitation of the geometric information has been coupled by the use of laser intensity, which may provide additional data for multiple purposes. This option has been emphasized by the availability of sensors working on different wavelength, thus able to provide additional information for classification of surfaces and objects. Several applications ofmonochromatic and multi-spectral LiDAR data have been already developed in different fields: geosciences, agriculture, forestry, building and cultural heritage. The use of intensity data to extract measures of point cloud quality has been also developed. The paper would like to give an overview on the state-of-the-art of these techniques, and to present the modern technologies for the acquisition of multispectral LiDAR data. In addition, the ISPRS WG III/5 on ‘Information Extraction from LiDAR Intensity Data’ has collected and made available a few open data sets to support scholars to do research on this field. This service is presented and data sets delivered so far as are described.

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Section: Lidar Intensity As a Quality Measurementioning

confidence: 90%

Methods From Information Extraction From Lidar Intensity Data and Multispectral Lidar Technology

Scaioni

Höfle

Kersting

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…This is the case for some large manufacturers (Z + F, Leica, Wetzlar, Germany). For laser scanners from brands that do not offer these possibilities, other approaches [20,21] can be chosen. The precision determined with this approach includes the influences of the distance measurement, the angle of incidence and the object properties.…”

Section: Forward Modeling-quality Analysis Of 3d Point Clouds Derivedmentioning

confidence: 99%

“…Backward modeling approaches are mainly 3D point clouds to point cloud comparisons (Cloud2Cloud) [19]. Surface based approaches are shown in [20,21]. The comparison of captured 3D point clouds to highly accurate 3D reference point clouds [22] is suitable here to investigate the accuracy.…”

mentioning

confidence: 99%

High-Precision 3D Object Capturing with Static and Kinematic Terrestrial Laser Scanning in Industrial Applications—Approaches of Quality Assessment

Stenz¹,

Hartmann

Paffenholz

et al. 2020

Remote Sensing

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Terrestrial laser scanning is used in many disciplines of engineering. Examples include mobile mapping, architecture surveying, archaeology, as well as monitoring and surveillance measurements. For most of the mentioned applications, 3D object capturing in an accuracy range of several millimeters up to a few centimeters is sufficient. However, in engineering geodesy, particularly in industrial surveying or monitoring measurements, accuracies in a range of a few millimeters are required. Additional increased quality requirements apply to these applications. This paper focuses on the quality investigation of data captured with static and kinematic terrestrial laser scanning. For this purpose, suitable sensors, which are typically used in the approach of a multi-sensor-system, as well as the corresponding data capturing/acquisition strategies, are presented. The aim of such systems is a geometry- and surface-based analysis in an industrial environment with an accuracy of +/− 1–2 mm or better.

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“…We have developed an empirical formula for the range precision ( ) computation based on fieldwork and validation studies given in our previous work (Ozendi et al, 2017). It takes into account the distance between the TLS and the point, incidence angle of the incoming laser beam, and reflectivity of the object surface.…”

Section: Computation Of the Range Precision Value /mentioning

confidence: 99%

Stochastic Surface Mesh Reconstruction

Özendi¹,

Akça

Topan³

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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A generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with developing an anisotropic point error model, which is capable of computing the theoretical precisions of 3D coordinates of each individual point in the point cloud. The magnitude and direction of the errors are represented in the form of error ellipsoids. The following second step is focused on the stochastic surface mesh reconstruction. It exploits the previously determined error ellipsoids by computing a point-wise quality measure, which takes into account the semi-diagonal axis length of the error ellipsoid. The points only with the least errors are used in the surface triangulation. The remaining ones are automatically discarded.

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A generic point error model for TLS derived point clouds

Cited by 12 publications

References 11 publications

Methods From Information Extraction From Lidar Intensity Data and Multispectral Lidar Technology

Methods From Information Extraction From Lidar Intensity Data and Multispectral Lidar Technology

High-Precision 3D Object Capturing with Static and Kinematic Terrestrial Laser Scanning in Industrial Applications—Approaches of Quality Assessment

Stochastic Surface Mesh Reconstruction

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