scholarly journals Integration of Laser Scanner and Photogrammetry for Heritage BIM Enhancement

2021 ◽  
Vol 10 (5) ◽  
pp. 316
Author(s):  
Yahya Alshawabkeh ◽  
Ahmad Baik ◽  
Yehia Miky
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Cost Effective ◽  
Point Clouds ◽  
Data Interpretation ◽  
Information Modeling ◽  
World Heritage Site ◽  
Architectural Features ◽  
House Museum

Digital 3D capture and reliable reproduction of architectural features is the first and most difficult step towards defining a heritage BIM. Three-dimensional digital survey technologies, such as TLS and photogrammetry, enable experts to scan buildings with a new level of detail. Challenges in the tracing of parametric objects in a TLS point cloud include the reconstruction of occluded parts, measurement of uncertainties relevant to surface reflectivity, and edge detection and location. In addition to image-based techniques being considered cost effective, highly flexible, and efficient in producing a high-quality 3D textured model, they also provide a better interpretation of surface linear characteristics. This article addresses an architecture survey workflow using photogrammetry and TLS to optimize a point cloud that is sufficient for a reliable HBIM. Fusion-based workflows were proposed during the recording of two heritage sites—the Matbouli House Museum in Historic Jeddah, a UNESCO World Heritage Site; and Asfan Castle. In the Matbouli House Museum building, which is rich with complex architectural features, multi-sensor recording was implemented at different resolutions and levels of detail. The TLS data were used to reconstruct the basic shape of the main structural elements, while the imagery’s superior radiometric data and accessibility were effectively used to enhance the TLS point clouds for improving the geometry, data interpretation, and parametric tracing of irregular objects in the facade. Furthermore, in the workflow that is considered to be the ragged terrain of the Castle of Asfan, here, the TLS point cloud was supplemented with UAV data in the upper building zones where the shadow data originated. Both datasets were registered using an ICP algorithm to scale the photogrammetric data and define their actual position in the construction system. The hybrid scans were imported and processed in the BIM environment. The building components were segmented and classified into regular and irregular surfaces, in order to perform detailed building information modeling of the architectural elements. The proposed workflows demonstrated an appropriate performance in terms of reliable and complete BIM mapping in the complex structures.

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 Protocol Development for Point Clouds, Triangulated Meshes and Parametric Model Acquisition and Integration in an HBIM Workflow for Change Control and Management in a UNESCO’s World Heritage Site

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1083
Author(s):  
Adela Rueda Márquez de la Plata ◽  
Pablo Alejandro Cruz Franco ◽  
Jesús Cruz Franco ◽  
Victor Gibello Bravo
Keyword(s):  
Urban Area ◽  
Residential Buildings ◽  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
World Heritage ◽  
World Heritage Site ◽  
Heritage Site ◽  
Unesco World Heritage Site

This article illustrates a data acquisition methodological process based on Structure from Motion (SfM) processing confronted with terrestrial laser scanner (TLS) and integrated into a Historic Building Information Model (HBIM) for architectural Heritage’s management. This process was developed for the documentation of Cáceres’ Almohad wall bordering areas, a UNESCO World Heritage Site. The case study’s aim was the analysis, management and control of a large urban area where the urban growth had absorbed the wall, making it physically inaccessible. The methodology applied was the combination of: clouds and meshes obtained by SfM; with images acquired from Unmanned Aerial Vehicle (UAV) and Single Lens Reflex (SLR) and terrestrial photogrammetry; and finally, with clouds obtained by TLS. The outcome was a smart-high-quality three-dimensional study model of the inaccessible urban area. The final result was two-fold. On one side, there was a methodological result, a low cost and accurate smart work procedure to obtain a three-dimensional parametric HBIM model that integrates models obtained by remote sensing. On the other side, a patrimonial result involved the discovery of a XII century wall’s section, that had supposedly been lost, that was hidden among the residential buildings. The article covers the survey campaign carried out by the research team and the techniques applied.

scholarly journals Study on Real-Time Point Cloud Superimposition on Camera Image to Assist Environmental Three-Dimensional Laser Scanning

2021 ◽  
Vol 15 (3) ◽  
pp. 324-333
Author(s):  
Kenta Ohno ◽  
Hiroaki Date ◽  
Satoshi Kanai ◽  
◽  
Keyword(s):  
Real Time ◽  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Laser Measurements ◽  
Attitude Error ◽  
Camera Image ◽  
Actual Environment

Recently, three-dimensional (3D) laser scanning technology using terrestrial laser scanner (TLS) has been widely used in the fields of plant manufacturing, civil engineering and construction, and surveying. It is desirable for the operator to be able to immediately and intuitively confirm the scanned point cloud to reduce unscanned regions and acquire scanned point clouds of high quality. Therefore, in this study, we developed a method to superimpose the point cloud on the actual environment to assist environmental 3D laser measurements, allowing the operator to check the scanned point cloud or unscanned regions in real time using the camera image. The method included extracting the correspondences of the camera image and the image generated by point clouds by considering unscanned regions, estimating the camera position and attitude in the point cloud by sampling correspondence points, and superimposing the scanned point cloud and unscanned regions on the camera image. When the proposed method was applied to two types of environments, that is, a boiler room and university office, the estimated camera image had a mean position error of approximately 150 mm and mean attitude error of approximately 1°, while the scanned point cloud and unscanned regions were superimposed on the camera image on a tablet PC at a rate of approximately 1 fps.

scholarly journals A DIGITAL ARCHIVE OF BOROBUDUR BASED ON 3D POINT CLOUDS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 577-582
Author(s):  
M. Kawato ◽  
L. Li ◽  
K. Hasegawa ◽  
M. Adachi ◽  
H. Yamaguchi ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
World Heritage Site ◽  
Digital Archive ◽  
First Person ◽  
3D Point Cloud ◽  
3D Point Clouds ◽  
The Temple

Abstract. Three-dimensional point clouds are becoming popular representations for digital archives of cultural heritage sites. The Borobudur Temple, located in Central Java, Indonesia, was built in the 8th century. Borobudur is considered one of the greatest Buddhist monuments in the world and was listed as a UNESCO World Heritage site. We are developing a virtual reality system as a digital archive of the Borobudur Temple. This research is a collaboration between Ritsumeikan University, Japan, the Indonesian Institute of Sciences (LIPI), and the Borobudur Conservation Office, Indonesia. In our VR system, the following three data sources are integrated to form a 3D point cloud: (1) a 3D point cloud of the overall shape of the temple acquired by photogrammetry using a camera carried by a UAV, (2) a 3D point cloud obtained from precise photogrammetric measurements of selected parts of the temple building, and (3) 3D data of the hidden relief panels recovered from the archived 2D monocular photos using deep learning. Our VR system supports both the first-person view and the bird’s eye view. The first-person view allows immersive observation and appreciation of the cultural heritage. The bird’s eye view is useful for understanding the whole picture. A user can easily switch between the two views by using a user-friendly VR user interface constructed by a 3D game engine.

Handheld Laser Scanner Research

2019 ◽  
Vol 952 (10) ◽  
pp. 47-54
Author(s):  
A.V. Komissarov ◽  
A.V. Remizov ◽  
M.M. Shlyakhova ◽  
K.K. Yambaev
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Test Site ◽  
Optical Systems ◽  
Advantages And Disadvantages ◽  
Site Survey ◽  
Laser Scanners ◽  
Three Dimensional Models ◽  
The Stability

The authors consider hand-held laser scanners, as a new photogrammetric tool for obtaining three-dimensional models of objects. The principle of their work and the newest optical systems based on various sensors measuring the depth of space are described in detail. The method of simultaneous navigation and mapping (SLAM) used for combining single scans into point cloud is outlined. The formulated tasks and methods for performing studies of the DotProduct (USA) hand-held laser scanner DPI?8X based on a test site survey are presented. The accuracy requirements for determining the coordinates of polygon points are given. The essence of the performed experimental research of the DPI?8X scanner is described, including scanning of a test object at various scanner distances, shooting a test polygon from various scanner positions and building point cloud, repeatedly shooting the same area of the polygon to check the stability of the scanner. The data on the assessment of accuracy and analysis of research results are given. Fields of applying hand-held laser scanners, their advantages and disadvantages are identified.

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 Multi-Dimensional Underwater Point Cloud Detection Based on Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 884
Author(s):  
Chia-Ming Tsai ◽  
Yi-Horng Lai ◽  
Yung-Da Sun ◽  
Yu-Jen Chung ◽  
Jau-Woei Perng
Keyword(s):  
Deep Learning ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Training Data ◽  
Network Architectures ◽  
Point Cloud Data ◽  
Data Types ◽  
Raw Data ◽  
Cloud Data

Numerous sensors can obtain images or point cloud data on land, however, the rapid attenuation of electromagnetic signals and the lack of light in water have been observed to restrict sensing functions. This study expands the utilization of two- and three-dimensional detection technologies in underwater applications to detect abandoned tires. A three-dimensional acoustic sensor, the BV5000, is used in this study to collect underwater point cloud data. Some pre-processing steps are proposed to remove noise and the seabed from raw data. Point clouds are then processed to obtain two data types: a 2D image and a 3D point cloud. Deep learning methods with different dimensions are used to train the models. In the two-dimensional method, the point cloud is transferred into a bird’s eye view image. The Faster R-CNN and YOLOv3 network architectures are used to detect tires. Meanwhile, in the three-dimensional method, the point cloud associated with a tire is cut out from the raw data and is used as training data. The PointNet and PointConv network architectures are then used for tire classification. The results show that both approaches provide good accuracy.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals VALIDATION OF A UAV-DERIVED POINT CLOUD BY SEMANTIC CLASSIFICATION AND COMPARISON WITH TLS DATA

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 83-90
Author(s):  
M. Franzini ◽  
V. Casella ◽  
P. Marchese ◽  
M. Marini ◽  
G. Della Porta ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Point Clouds ◽  
Aerial Survey ◽  
Gradual Transition ◽  
Support Vector ◽  
Uniform Density ◽  
Mutual Distance ◽  
Semantic Classification ◽  
Cost Efficient

Abstract. Recent years showed a gradual transition from terrestrial to aerial survey thanks to the development of UAV and sensors for it. Many sectors benefited by this change among which geological one; drones are flexible, cost-efficient and can support outcrops surveying in many difficult situations such as inaccessible steep and high rock faces. The experiences acquired in terrestrial survey, with total stations, GNSS or terrestrial laser scanner (TLS), are not yet completely transferred to UAV acquisition. Hence, quality comparisons are still needed. The present paper is framed in this perspective aiming to evaluate the quality of the point clouds generated by an UAV in a geological context; data analysis was conducted comparing the UAV product with the homologous acquired with a TLS system. Exploiting modern semantic classification, based on eigenfeatures and support vector machine (SVM), the two point clouds were compared in terms of density and mutual distance. The UAV survey proves its usefulness in this situation with a uniform density distribution in the whole area and producing a point cloud with a quality comparable with the more traditional TLS systems.

scholarly journals INTEGRATING TOPOGRAPHIC, PHOTOGRAMMETRIC AND LASER SCANNING TECHNIQUES FOR A SCAN-TO-BIM PROCESS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 883-890
Author(s):  
M. Lo Brutto ◽  
E. Iuculano ◽  
P. Lo Giudice
Keyword(s):  
Laser Scanning ◽  
Building Information Modeling ◽  
Laser Scanner ◽  
Point Clouds ◽  
Parametric Modeling ◽  
Information Modeling ◽  
Survey Method ◽  
The Real ◽  
Building Information ◽  
Heritage Building

Abstract. The preservation of historic buildings can often be particularly difficult due to the lack of detailed information about architectural features, construction details, etc.. However, in recent years considerable technological innovation in the field of Architecture, Engineering, and Construction (AEC) has been achieved by the Building Information Modeling (BIM) process. BIM was developed as a methodology used mainly for new construction but, given its considerable potential, this approach can also be successfully used for existing buildings, especially for buildings of historical and architectural value. In this case, it is more properly referred to as Historic – or Heritage – Building Information Modeling (HBIM). In the HBIM process, it is essential to precede the parametric modeling phase of the building with a detailed 3D survey that allows the acquisition of all geometric information. This methodology, called Scan-to-BIM, involves the use of 3D survey techniques for the production of point clouds as a geometric “database” for parametric modeling. The Scan-to-BIM approach can have several issues relating to the complexity of the survey. The work aims to apply the Scan-to-BIM approach to the survey and modeling of a historical and architectural valuable building to test a survey method, based on integrating different techniques (topography, photogrammetry and laser scanning), that improves the data acquisition phase. The “Real Cantina Borbonica” (Cellar of Royal House of Bourbon) in Partinico (Sicily, Italy) was chosen as a case study. The work has allowed achieving the HBIM of the “Real Cantina Borbonica” and testing an approach based exclusively on a topographic constraint to merge in the same reference system all the survey data (laser scanner and photogrammetric point clouds).

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