scholarly journals 3D Laser Scanner for Tunnel Surveying and Accuracy Analysis According to Registration Method

2019 ◽  
Vol 6 (1) ◽  
pp. 13-18
Author(s):  
Joon Kyu Park ◽  
Keyword(s):  
Laser Scanner ◽  
Accuracy Analysis ◽  
Registration Method

scholarly journals On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3908 ◽  
Author(s):  
Pavan Kumar B. N. ◽  
Ashok Kumar Patil ◽  
Chethana B. ◽  
Young Ho Chai
Keyword(s):  
Computer Aided Design ◽  
Point Cloud ◽  
Laser Scanner ◽  
Video Frame ◽  
Cad Model ◽  
Point Cloud Data ◽  
Registration Method ◽  
Industrial Facilities ◽  
Cloud Data ◽  
Generic Framework

Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment. This work also proposes a virtual interactive retrofitting framework that uses pre-defined 3D computer-aided design models (CAD) with a customized graphical user interface (GUI) and visualization of a 4-in-1 aligned video scene from a UAV camera in a desktop environment. Trials were carried out using the proposed framework in a real environment at a water treatment facility. A qualitative and quantitative study was conducted to evaluate the performance of the proposed generic framework from participants by adopting the appropriate questionnaire and retrofitting task-oriented experiment. Overall, it was found that the proposed framework could be a solution for interactive 3D CAD model retrofitting on a combination of UAV sensory setup-acquired PCD and real-time video from the camera in heavy industrial facilities.

scholarly journals Accuracy Analysis Of Three Dimensional Models Of Building Prof. H. Soedarto S. H. Using The Terrestrial Laser Scanner Technology Based On Traverse Method

Teknik ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 94
Author(s):  
Yudo Prasetyo
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Accuracy Analysis ◽  
Dimensional Models ◽  
Data Point ◽  
Three Dimensional Models

Teknologi dokumentasi gedung secara spasial untuk konservasi dan perencanaan tata ruang semakin berkembang pesat. Urgensi tingkat ketelitian dalam suatu pengukuran juga dituntut semakin tinggi. Salah satu teknologi pembentukan objek tiga dimensi yang berkembang saat ini adalah Terrestrial Laser Scanner (TLS). Metode pengukuran TLS terdiri atas 4 metode yaitu: Cloud to Cloud, Target to Target, Traverse, dan metode kombinasi. Penelitian ini bertujuan untuk menganalisa tingkat ketelitian metode Traverse dalam pengukuran suatu objek model tiga dimensi untuk keperluan dokumentasi gedung menggunakan TLS.Ketelitian metode Traverse akan diujikan pada Gedung Prof. H. Soedarto, S. H. Tingkat ketelitiannya diujikan pada dua parameter yakni hasil metode registrasi dan hasil visualisasi model tiga dimensi. Hasil analisis pengolahan data point cloud menunjukkan bahwa alat TLS dengan metode Traverse dapat digunakan untuk menghasilkan model tiga dimensi Gedung Prof. Sudarto, S. H. Nilai rata-rata validasi yang diperoleh adalah sebesar 0,004 meter dengan besaran ketelitian model RMSE sebesar ±0,00611 meter. 

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.

ADAPTION OF INVARIANT FEATURES IN IMAGE FOR POINT CLOUDS REGISTRATION

2015 ◽  
Vol 75 (10) ◽  
Author(s):  
Mohd Azwan Abbas ◽  
Halim Setan ◽  
Zulkepli Majid ◽  
Albert K. Chong ◽  
Lau Chong Luh ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Scale Invariant ◽  
Registration Method ◽  
Flat Surfaces ◽  
Invariant Features ◽  
Limited Class ◽  
Coarse Registration ◽  
Straight Lines ◽  
Scale Invariant Feature

Currently, coarse registration methods for scanner are required heavy operator intervention either before or after scanning process. There also have an automatic registration method but only applicable to a limited class of objects (e.g. straight lines and flat surfaces). This study is devoted to a search of a computationally feasible automatic coarse registration method with a broad range of applicability. Nowadays, most laser scanner systems are supplied with a camera, such that the scanned data can also be photographed. The proposed approach will exploit the invariant features detected from image to associate point cloud registration. Three types of detectors are included: scale invariant feature transform (SIFT), 2) Harris affine, and 3) maximally stable extremal regions (MSER). All detected features will transform into the laser scanner coordinate system, and their performance is measured based on the number of corresponding points. Several objects with different observation techniques were performed to evaluate the capability of proposed approach and also to evaluate the performance of selected detectors.  

scholarly journals GLOBAL REFINEMENT OF TERRESTRIAL LASER SCANNER DATA REGISTRATION USING WEIGHTED SENSOR POSES

2018 ◽  
Vol XLII-1 ◽  
pp. 121-125
Author(s):  
D. R. dos Santos ◽  
F. P. Freiman ◽  
N. L. Pavan
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Outdoor Environment ◽  
Terrestrial Laser Scanner ◽  
Positional Accuracy ◽  
Registration Method ◽  
Data Registration ◽  
Registration Errors ◽  
Refinement Method ◽  
Industrial Projects

<p><strong>Abstract.</strong> Terrestrial laser scanner (TLS) sensor captures highly dense and accurate point clouds quite useful for indoor and outdoor mapping, navigation, 3D reconstruction, surveillance, industrial projects, infrastructure management, and others. In this paper, we present a global registration method that weights the sensor poses for refinement of TLS data registration. Our global refinement method assumes that the variance-covariance matrix that describes the uncertainty of sensor poses is available to refine the registration errors. The effectiveness of the proposed method is demonstrated with TLS dataset obtained into outdoor environment. Our results show that the weighting the sensor poses obtained in registration task improves the positional accuracy of TLS sensor.</p>

scholarly journals RESEARCH ON THE DIGITAL RETENTION MECHANISM OF TIBETAN BUDDHISM ARCHITECTURE BASED ON UAV AND TLS: A CASE STUDY OF BAOGUANG HALL

2021 ◽  
Vol VIII-M-1-2021 ◽  
pp. 95-100
Author(s):  
Z. Li ◽  
M. Hou ◽  
Y. Dong ◽  
J. Wang ◽  
Y. Ji ◽  
...  
Keyword(s):  
Point Cloud ◽  
Cloud Model ◽  
Laser Scanner ◽  
Retention Mechanism ◽  
Point Cloud Data ◽  
Architectural Heritage ◽  
Registration Method ◽  
Cloud Data ◽  
3D Information ◽  
Unique Style

Abstract. Tibetan Buddhist architecture embodies ancient Chinese architectural culture and religious culture. In the past, the information retention mechanisms for ancient buildings were implemented as photos, tracings, and rubbings, which cannot fundamentally document the authenticity of architectural heritage. To explore the digital retention method for the unique style of Han Tibetan architecture，this research that based on the idea of reverse documentation first collects point cloud data with the technical support of unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanner (TLS) and then uses registration method to obtain the integral of the point cloud model of Baoguang Hall. This paper explores the possibility of extracting 2D and 3D information, such as architectural plans, facades, decorative components, and models of the temple architecture, by processing point cloud data. Finally, this study proves the feasibility of using digital technology for the preservation and protection of architectural heritage.

scholarly journals Some Remarks on Registration Techniques of Point Clouds Obtained from Terrestrial Laser Scanning

2021 ◽  
Vol 906 (1) ◽  
pp. 012078
Author(s):  
Zbigniew Muszyński ◽  
Paulina Kujawa
Keyword(s):  
Reference Frame ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Engineering Structures ◽  
Registration Method ◽  
Railway Line ◽  
Local Reference ◽  
High Level

Abstract Terrestrial laser scanning (TLS) is a measurement technique used for many geodetic applications (such as determination of displacement and deformation of building objects or monitoring of engineering structures) as well as for non-geodetic applications (for example in forestry, archeology or geotechnics). Despite the high level of automation, the measurement with a laser scanner and the processing of the results consist of many stages and depend on many factors. The most important factors are: the features of measurement object (size, material, availability), required accuracy, speed of scanning, required scan density, type of reference frame, registration method, planned visualization, and 3D modelling method. In this article, the authors focused on the type of registration technique of point clouds obtained from TLS. The most popular strategies of registration were discussed. The practical application of the selected technique was presented on the example of measurement of the railway gauge of the viaduct. Due to the characteristic object (narrow and long railway line) and considering the local reference frame of point clouds as well as the need of minimization of the measurement time, the hybrid registration method in the nested variant was selected.

Registration of Point-Clouds from Terrestrial and Portable Laser Scanners

2016 ◽  
Vol 10 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Takuma Watanabe ◽  
◽  
Takeru Niwa ◽  
Hiroshi Masuda ◽  
Keyword(s):  
Point Cloud ◽  
Short Range ◽  
Large Scale ◽  
Laser Scanner ◽  
Point Clouds ◽  
Limited Region ◽  
Registration Method ◽  
Laser Scanners ◽  
Scale Point ◽  
Candidate Regions

We proposed a registration method for aligning short-range point-clouds captured using a portable laser scanner (PLS) to a large-scale point-cloud captured using a terrestrial laser scanner (TLS). As a PLS covers a very limited region, it often fails to provide sufficient features for registration. In our method, the system analyzes large-scale point-clouds captured using a TLS and indicates candidate regions to be measured using a PLS. When the user measures a suggested region, the system aligns the captured short-range point-cloud to the large-scale point-cloud. Our experiments show that the registration method can adequately align point-clouds captured using a TLS and a PLS.

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