Skeleton-based 3D reconstruction of as-built pipelines from laser-scan data

Lee, Joohyuk; Son, Hyojoo; Kim, Changmin; Kim, Chang-Wan

doi:10.1016/j.autcon.2013.05.009

Cited by 102 publications

(30 citation statements)

References 18 publications

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“…While planarity is important for reconstructing beams, their elongated shape and connectedness between beams suggests to consider previous work on piping installations. The automatic reconstruction of piping installations from point clouds has been performed by several authors (Rabbani et al, 2007;Lee et al, 2013). In a first step, the point cloud is split into groups using segmentation, clustering, and/or skeletonization.…”

Section: Problem Statement and Related Workmentioning

confidence: 99%

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Pöchtrager

Styhler-Aydın

Döring-Williams

et al. 2017

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

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ABSTRACT:The analysis of historic roof constructions is an important task for planning the adaptive reuse of buildings or for maintenance and restoration issues. Current approaches to modeling roof constructions consist of several consecutive operations that need to be done manually or using semi-automatic routines. To increase efficiency and allow the focus to be on analysis rather than on data processing, a set of methods was developed for the fully automated analysis of the roof constructions, including integration of architectural and structural modeling. Terrestrial laser scanning permits high-detail surveying of large-scale structures within a short time. Whereas 3-D laser scan data consist of millions of single points on the object surface, we need a geometric description of structural elements in order to obtain a structural model consisting of beam axis and connections. Preliminary results showed that the developed methods work well for beams in flawless condition with a quadratic cross section and no bending. Deformations or damages such as cracks and cuts on the wooden beams can lead to incomplete representations in the model. Overall, a high degree of automation was achieved.

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Section: Problem Statement and Related Workmentioning

confidence: 99%

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Pöchtrager

Styhler-Aydın

Döring-Williams

et al. 2017

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

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“…Recently, improving the level of details in as-built is recognised as an open question [7,9]. On the other hand, integration of the detected fine objects and the data into BIM as a new paradigm of a knowledge sharing system is still challenging, and the use of appropriate hardware, structure, and ad-hoc algorithm still needs to be enhanced [7,10].…”

Section: Introductionmentioning

confidence: 99%

Utilisation of a New Terrestrial Scanner for Reconstruction of As-Built Models: A Comparative Study

Sepasgozar¹,

Lim²,

Shirowzhan³

et al. 2015

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Recent studies show a great potential of improving construction productivity through using real-time applications to measure change orders and other objects to create as-built. As an enhancement to this promising concept, this paper presents the process of implementation of an efficient framework for as-built Building Information Modelling (BIM) using a new Scan Station that enables contractors to acquire accurate data and create and update the asbuilt models. A novel framework designed and assisted in the conversion of the raw 3D point cloud data from a laser scanner positioned at multiple locations of a facility into a compact and semantically rich model. The result of the study was compared with two other as-built models using mobile and terrestrial lidar scanners to understand the capability of each for building information modelling. It was found that the framework using the new Scan Station has a great potential to collect accurate data that can be transferred to BIM for creating as-built models. The results show that the accuracy of fine objects' dimensions varies from -2% to +2%. The comparison of the test results with our previous experiments using different scanners shows that every scanner has its own advantage for each job in construction.

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“…Recently, improving the level of details in as-built is recognised as an open question [3,10]. On the other hand, integration of the detected fine objects and the data into BIM as a new paradigm of a knowledge sharing system is still challenging, and the use of appropriate hardware, structure, and ad-hoc algorithm still needs to be enhanced [3,11].…”

Section: Introductionmentioning

confidence: 99%

Implementation of As-Built Information Modelling UsingMobile and Terrestrial Lidar Systems

Sepasgozar¹,

Lim²,

Shirowzhan³

et al. 2014

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-Recently it is observed that there is an increasing trend of using lidar point clouds in construction, since lidar is able to provide highly accurate 3-dimensional representations of objects. The flip side of a lidar point cloud is its massive size and therefore prolonged time for data processing. Our research aims to develop an efficient framework for as-built modelling in terms of time, cost and performance. For this, we collected lidar point clouds using two different data collection methods (i.e. mobile and terrestrial lidar systems with a few centimetre level accuracy) and constructed solid 3-dimensional models of a building. The procedures of creating asbuilt models from both data acquisition methods are compared to understand the capability of each for automatic building information modelling. In order to create as-built models, a framework consisting of eight key stages from data capturing to constructing the building information model is developed. It was found that the framework using mobile lidar enables contractors to create as-built models for complex objects in a timely manner, whereas the framework using terrestrial lidar provides us with more accurate as-built information models. The implementation results of the two frameworks using mobile and terrestrial lidar systems vary between 5-30 mm and 1-45 mm, respectively. It is anticipated that the proposed study becomes a step forward to full automation of lidar-based building information modelling.

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Skeleton-based 3D reconstruction of as-built pipelines from laser-scan data

Cited by 102 publications

References 18 publications

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Utilisation of a New Terrestrial Scanner for Reconstruction of As-Built Models: A Comparative Study

Implementation of As-Built Information Modelling UsingMobile and Terrestrial Lidar Systems

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