Pairwise registration for terrestrial laser scanner point clouds based on the covariance matrix

2021 ◽  
Vol 12 (8) ◽  
pp. 788-798
Author(s):  
Yongjian Fu ◽  
Zongchun Li ◽  
Yong Deng ◽  
Shihang Zhang ◽  
Hua He ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Pairwise Registration

scholarly journals Fitting Terrestrial Laser Scanner Point Clouds with T-Splines: Local Refinement Strategy for Rigid Body Motion

2021 ◽  
Vol 13 (13) ◽  
pp. 2494
Author(s):  
Gaël Kermarrec ◽  
Niklas Schild ◽  
Jan Hartmann
Keyword(s):  
Point Cloud ◽  
Goodness Of Fit ◽  
Laser Scanner ◽  
Point Clouds ◽  
Statistical Testing ◽  
Computational Time ◽  
Terrestrial Laser Scanner ◽  
Reference Surface ◽  
Local Refinement ◽  
Surface Approximation

T-splines have recently been introduced to represent objects of arbitrary shapes using a smaller number of control points than the conventional non-uniform rational B-splines (NURBS) or B-spline representatizons in computer-aided design, computer graphics and reverse engineering. They are flexible in representing complex surface shapes and economic in terms of parameters as they enable local refinement. This property is a great advantage when dense, scattered and noisy point clouds are approximated using least squares fitting, such as those from a terrestrial laser scanner (TLS). Unfortunately, when it comes to assessing the goodness of fit of the surface approximation with a real dataset, only a noisy point cloud can be approximated: (i) a low root mean squared error (RMSE) can be linked with an overfitting, i.e., a fitting of the noise, and should be correspondingly avoided, and (ii) a high RMSE is synonymous with a lack of details. To address the challenge of judging the approximation, the reference surface should be entirely known: this can be solved by printing a mathematically defined T-splines reference surface in three dimensions (3D) and modeling the artefacts induced by the 3D printing. Once scanned under different configurations, it is possible to assess the goodness of fit of the approximation for a noisy and potentially gappy point cloud and compare it with the traditional but less flexible NURBS. The advantages of T-splines local refinement open the door for further applications within a geodetic context such as rigorous statistical testing of deformation. Two different scans from a slightly deformed object were approximated; we found that more than 40% of the computational time could be saved without affecting the goodness of fit of the surface approximation by using the same mesh for the two epochs.

scholarly journals Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 201
Author(s):  
Michael Bekele Maru ◽  
Donghwan Lee ◽  
Kassahun Demissie Tola ◽  
Seunghee Park
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Depth Camera ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
3D Point Clouds ◽  
3D Information

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

scholarly journals Explanation for the seam line discontinuity in terrestrial laser scanner point clouds

2019 ◽  
Vol 154 ◽  
pp. 59-69 ◽  
Author(s):  
D.D. Lichti ◽  
C.L. Glennie ◽  
K. Al-Durgham ◽  
A. Jahraus ◽  
J. Steward
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner

scholarly journals Displacement Study of a Large-Scale Freeform Timber Plate Structure Using a Total Station and a Terrestrial Laser Scanner

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 413 ◽  
Author(s):  
Anh Chi Nguyen ◽  
Yves Weinand
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Laser Scanner ◽  
Experimental Tests ◽  
Point Clouds ◽  
Element Model ◽  
Experimental Investigations ◽  
Bottom Surface ◽  
Terrestrial Laser Scanner ◽  
Total Station

Recent advances in timber construction have led to the realization of complex timber plate structures assembled with wood-wood connections. Although advanced numerical modelling tools have been developed to perform their structural analysis, limited experimental tests have been carried out on large-scale structures. However, experimental investigations remain necessary to better understand their mechanical behaviour and assess the numerical models developed. In this paper, static loading tests performed on timber plate shells of about 25 m span are reported. Displacements were measured at 16 target positions on the structure using a total station and on its entire bottom surface using a terrestrial laser scanner. Both methods were compared to each other and to a finite element model in which the semi-rigidity of the connections was represented by springs. Total station measurements provided more consistent results than point clouds, which nonetheless allowed the visualization of displacement fields. Results predicted by the model were found to be in good agreement with the measurements compared to a rigid model. The semi-rigid behaviour of the connections was therefore proven to be crucial to precisely predict the behaviour of the structure. Furthermore, large variations were observed between as-built and designed geometries due to the accumulation of fabrication and construction tolerances.

Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring

2019 ◽  
Vol 13 (2) ◽  
pp. 105-134 ◽  
Author(s):  
Mohammad Omidalizarandi ◽  
Boris Kargoll ◽  
Jens-André Paffenholz ◽  
Ingo Neumann
Keyword(s):  
Em Algorithm ◽  
Laser Scanner ◽  
Digital Camera ◽  
Point Clouds ◽  
Deformation Monitoring ◽  
Deformation Analysis ◽  
Terrestrial Laser Scanner ◽  
External Calibration ◽  
3D Point Clouds ◽  
Calibration Parameters

Abstract In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two.

scholarly journals Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds

2016 ◽  
Vol 18 (1) ◽  
pp. 111-132 ◽  
Author(s):  
Alexandre Escolà ◽  
José A. Martínez-Casasnovas ◽  
Josep Rufat ◽  
Jaume Arnó ◽  
Amadeu Arbonés ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Extract Information

scholarly journals Finding the next-best scanner position for as-built modeling of piping systems

2014 ◽  
Vol XL-5 ◽  
pp. 313-320 ◽  
Author(s):  
K. Kawashima ◽  
S. Yamanishi ◽  
S. Kanai ◽  
H. Date
Keyword(s):  
A Priori ◽  
Laser Scanner ◽  
Point Clouds ◽  
Computational Time ◽  
Piping System ◽  
Terrestrial Laser Scanner ◽  
View Planning ◽  
Piping Systems ◽  
Petroleum Refineries ◽  
Priori Information

Renovation of plant equipment of petroleum refineries or chemical factories have recently been frequent, and the demand for 3D asbuilt modelling of piping systems is increasing rapidly. Terrestrial laser scanners are used very often in the measurement for as-built modelling. However, the tangled structures of the piping systems results in complex occluded areas, and these areas must be captured from different scanner positions. For efficient and exhaustive measurement of the piping system, the scanner should be placed at optimum positions where the occluded parts of the piping system are captured as much as possible in less scans. However, this "nextbest" scanner positions are usually determined by experienced operators, and there is no guarantee that these positions fulfil the optimum condition. Therefore, this paper proposes a computer-aided method of the optimal sequential view planning for object recognition in plant piping systems using a terrestrial laser scanner. In the method, a sequence of next-best positions of a terrestrial laser scanner specialized for as-built modelling of piping systems can be found without any a priori information of piping objects. Different from the conventional approaches for the next-best-view (NBV) problem, in the proposed method, piping objects in the measured point clouds are recognized right after an every scan, local occluded spaces occupied by the unseen piping systems are then estimated, and the best scanner position can be found so as to minimize these local occluded spaces. The simulation results show that our proposed method outperforms a conventional approach in recognition accuracy, efficiency and computational time.

scholarly journals Global Registration of Terrestrial Laser Scanner Point Clouds Using Plane-to-Plane Correspondences

2020 ◽  
Vol 12 (7) ◽  
pp. 1127
Author(s):  
Nadisson Luis Pavan ◽  
Daniel Rodrigues dos Santos ◽  
Kourosh Khoshelham
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Information Modeling ◽  
Coordinate Frame ◽  
Complex Numbers ◽  
Terrestrial Laser Scanner ◽  
Registration Method ◽  
Matching Algorithm ◽  
Global Registration ◽  
Global Consistency

Registration of point clouds is a central problem in many mapping and monitoring applications, such as outdoor and indoor mapping, high-speed railway track inspection, heritage documentation, building information modeling, and others. However, ensuring the global consistency of the registration is still a challenging task when there are multiple point clouds because the different scans should be transformed into a common coordinate frame. The aim of this paper is the registration of multiple terrestrial laser scanner point clouds. We present a plane-based matching algorithm to find plane-to-plane correspondences using a new parametrization based on complex numbers. The multiplication of complex numbers is based on analysis of the quadrants to avoid the ambiguity in the calculation of the rotation angle formed between normal vectors of adjacent planes. As a matching step may contain several matrix operations, our strategy is applied to reduce the number of mathematical operations. We also design a novel method for global refinement of terrestrial laser scanner data based on plane-to-plane correspondences. The rotation parameters are globally refined using operations of quaternion multiplication, while the translation parameters are refined using the parameters of planes. The global refinement is done non-iteratively. The experimental results show that the proposed plane-based matching algorithm efficiently finds plane correspondences in partial overlapping scans providing approximate values for the global registration, and indicate that an accuracy better than 8 cm can be achieved by using our global fine plane-to-plane registration method.

Sign in / Sign up

Export Citation Format

Share Document