A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Mukupa, Wallace; Roberts, Gethin Wyn; Hancock, Craig M.; Al-Manasir, Khalil

doi:10.1080/00396265.2015.1133039

Cited by 143 publications

(152 citation statements)

References 44 publications

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“…In contrast to the subset and control point approaches, even more robustness is gained, if the whole point cloud spans a larger subspace of the three-dimensional space than any of its subsets. This approach is especially employed in change detection, for point clouds obtained from TLS measurements [20]. In these cases, the frequency of scans is high compared to the rate of change in the sense that the changes are so slow that displacement fields can be calculated for deformation monitoring.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods

et al. 2017

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Accurate three-dimensional (3D) data from indoor spaces are of high importance for various applications in construction, indoor navigation and real estate management. Mobile scanning techniques are offering an efficient way to produce point clouds, but with a lower accuracy than the traditional terrestrial laser scanning (TLS). In this paper, we first tackle the problem of how the quality of a point cloud should be rigorously evaluated. Previous evaluations typically operate on some point cloud subset, using a manually-given length scale, which would perhaps describe the ranging precision or the properties of the environment. Instead, the metrics that we propose perform the quality evaluation to the full point cloud and over all of the length scales, revealing the method precision along with some possible problems related to the point clouds, such as outliers, over-completeness and misregistration. The proposed methods are used to evaluate the end product point clouds of some of the latest methods. In detail, point clouds are obtained from five commercial indoor mapping systems, Matterport, NavVis, Zebedee, Stencil and Leica Pegasus: Backpack, and three research prototypes, Aalto VILMA , FGI Slammer and the Würzburg backpack. These are compared against survey-grade TLS point clouds captured from three distinct test sites that each have different properties. Based on the presented experimental findings, we discuss the properties of the proposed metrics and the strengths and weaknesses of the above mapping systems and then suggest directions for future research.

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Section: Introductionmentioning

confidence: 99%

Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods

et al. 2017

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“…In other words, TLS provides a remote sensing surveying technique with high speed, density, and accuracy, which makes it widely used in various fields within recent decades such as: 1. Engineering surveying, as topographical surveying (Lague et al, 2013), civil engineering surveying (Oskouie et al, 2016), deformation monitoring (Mukupa et al, 2016), and complex industrial equipment modelling (Son, 2014); 2. Architecture reconstruction (Santagati et al, 2013), heritage documentation and preservation (Fanti et al, 2013); 3.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

Jia

Lichti

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The optimal network design problem has been well addressed in geodesy and photogrammetry but has not received the same attention for terrestrial laser scanner (TLS) networks. The goal of this research is to develop a complete design system that can automatically provide an optimal plan for high-accuracy, large-volume scanning networks. The aim in this paper is to use three heuristic optimization methods, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO), to solve the first-order design (FOD) problem for a small-volume indoor network and make a comparison of their performances. The room is simplified as discretized wall segments and possible viewpoints. Each possible viewpoint is evaluated with a score table representing the wall segments visible from each viewpoint based on scanning geometry constraints. The goal is to find a minimum number of viewpoints that can obtain complete coverage of all wall segments with a minimal sum of incidence angles. The different methods have been implemented and compared in terms of the quality of the solutions, runtime and repeatability. The experiment environment was simulated from a room located on University of Calgary campus where multiple scans are required due to occlusions from interior walls. The results obtained in this research show that PSO and GA provide similar solutions while SA doesn't guarantee an optimal solution within limited iterations. Overall, GA is considered as the best choice for this problem based on its capability of providing an optimal solution and fewer parameters to tune.

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“…Appropriate methods are used for surveying of various objects, ranging from historic buildings to uninhabited territories for road construction [4,12,13]. Laser scanning systems collect data more completely and efficiently than traditional surveying methods [14].…”

Section: Discussionmentioning

confidence: 99%

Hybrid processing of laser scanning data

2018

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Abstract. In this article the analysis of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the base of usage of laser scanning data for historic building information modeling is presented. The results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application for the historical building of St. Petersburg Polytechnic University shows reliability of the proposed approaches.

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A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Cited by 143 publications

References 44 publications

Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods

Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

Hybrid processing of laser scanning data

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