Three-Dimensional (3D) As-Built Reconstruction from Laser Scanning Dataset

Razali, Ahmad Firdaus; Ariff, Mohd Farid Mohd; Majid, Zulkepli; Darwin, Norhadija; Aspuri, Anuar; Salleh, Mohd. Faizi Mohd.

doi:10.1109/icset51301.2020.9265360

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…This scanning process enables the collection of precise data about the landscape and its features. Compared to point-based data collection techniques employed by GNSS and total stations, TLS can capture and record 3D geospatial information [15].…”

Section: Terrestrial Laser Scanning (Tls)mentioning

confidence: 99%

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Transforming Physical Crime Scene into Geospatial-based Point Cloud Data

Azmil,

Mohd Ariff,

Razali

et al. 2024

Eng. Technol. Appl. Sci. Res.

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Terrestrial Laser Scanning (TLS) and Close-Range Photogrammetry (CRP) are advanced techniques for capturing 3D data in crime scene reconstruction, offering complementary information. Despite taking multiple scans and images from different angles to ensure a comprehensive model, limitations, such as device positioning, shadows, object distance, and laser beam angles prevent the creation of a complete crime scene model. Therefore, combining TLS and CRP data is crucial for achieving a comprehensive reconstruction. This study aims to transform a physical crime scene into a geospatial-based reconstructed model known as point clouds. The technique used was highly rich in realistic features, digitally reconstructed from TLS and CRP. The data sources were then fused via a rigid body transformation, creating a comprehensive crime scene model. The combined point cloud measurements were compared with measurements obtained from a high-precision Vernier caliper to ascertain their accuracy. The resulting Root Mean Square (RMSE) difference between the fused point cloud data and the high-precision caliper measurements was approximately ±4mm. The fusion of TLS and CRP data provides reliable and highly accurate 3D model point clouds, making it suitable for forensic applications.

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Section: Terrestrial Laser Scanning (Tls)mentioning

confidence: 99%

“…Point clouds are digital representations of real-world objects or structures, capturing detailed information, including RGB colors, dimensional measurements, sizes, and volumes [15,18]. They are generated using specialized lenses with LiDAR systems commonly found in TLSs [19].…”

Section: F Point Cloudmentioning

confidence: 99%

Transforming Physical Crime Scene into Geospatial-based Point Cloud Data

Azmil,

Mohd Ariff,

Razali

et al. 2024

Eng. Technol. Appl. Sci. Res.

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“…The integration of laser scanning and BIM technologies has been extensively studied in recent years, with several applications being identified in the construction industry. For example, laser scanning can be used to create as-built models of existing buildings for renovation and retrofitting projects [Woo et al 2010;Usmani et al 2020;Razali et al 2020]. The generated point cloud can also be used for clash detection and quality control during the construction phase, reducing the likelihood of errors and delays [Li et al 2020;Tan et al 2020].…”

Section: D Tools For the Documentation And Analysis Of Cultural Heritagementioning

confidence: 99%

3D Heterogeneous Database for Structural Analysis of Historic Buildings. A Discussion on Process Pipelines

Malik,

Garzulino,

Del Curto

2023

SDH

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This paper presents a methodology for creating a comprehensive heterogeneous 3D database for the structural evaluation of a historic building by using both non-destructive and destructive surveys combined with historical information. The availability of adequate data on the actual conditions is crucial when assessing the seismic vulnerability and structural behavior of a historic building and validating the results. A reliable 3D database must accept different kinds of data, e.g., the results of destructive/non-destructive surveys, historical information, etc. It must also be interrogated and enriched at any time. Therefore, creating such a 3D database may present several challenges in terms of data-gathering pipeline, comprehensiveness/redundancy, interpretation, organization, and integration with other heterogeneous data. The methodology we present in this paper includes 3D laser scanning, thermal imaging, and endoscopy combined with information regarding the state of conservation, construction history, materials, and techniques. We tested such methodology to create a database that was later used for Finite Element Modeling (FEM) to assess the seismic vulnerability of Diotti Palace, a neoclassical building that has been the seat of the Prefect of Milan since 1859. The results are analytically presented here. In conclusion, we highlight the pros and cons of the proposed methodology by means of a comparative discussion with the state of the art about 3D documentation pipelines for historic buildings and sites.

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“…Recently, 3D modelling representing interior of a building has gained attention from professionals in Architectural, Engineering, Construction (AEC) area. Due to its various benefits in facility management, building renovation, monitoring and restoration, many researchers and experts have been progressing to create a flexible, fast and affordable solution in creating this 3D model [1] [2]. Latest technology and innovation in building construction and monitoring like Building Information Modelling or BIM has increase the interest and development of 3D model representing existing, in-used building as well [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Data Collection Pipeline for Big Interior Registration and Modelling using 3D Sensor

Ismail,

Nathan,

Shukor

et al. 2023

J. Phys.: Conf. Ser.

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This paper highlights on the analysis of several data collection pipeline for big interior using Structure sensor. Data of big, large interior, collected by 3D sensors such as Structure sensor is very crucial and important as it could be used to develop 3D as-built model, where the model can be utilized for various purposes like maintenance, management as well as renovation work. However, collecting data of big interiors can be challenging as the outcome of the 3D model can be less accurate due to dimensions of the big interior which surpasses the range of the sensor. Thus, there is a need to have a proper planning when collecting 3D data representing big interior, especially rooms with clutter and occlusion due to furniture and equipment. This project concentrates on developing and testing suitable pipeline in collecting data representing big interior using Structure sensor. Three different methods were proposed, tested and analysed, where the interior is modelled using MeshLab. Results show that Method Two, which is wall by wall approach, is the most suitable among the other pipeline proposed. Thus, this method can be utilized by professionals and experts when using 3D sensors like Structure sensor in collecting big, large interior data.

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Three-Dimensional (3D) As-Built Reconstruction from Laser Scanning Dataset

Cited by 6 publications

References 25 publications

Transforming Physical Crime Scene into Geospatial-based Point Cloud Data

Transforming Physical Crime Scene into Geospatial-based Point Cloud Data

3D Heterogeneous Database for Structural Analysis of Historic Buildings. A Discussion on Process Pipelines

Data Collection Pipeline for Big Interior Registration and Modelling using 3D Sensor

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