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Automatic Object Detection from Digital Images by Deep Learning with Transfer Learning Read chapter Read first chapter

2018 | OriginalPaper | Chapter

3D Imaging in Construction and Infrastructure Management: Technological Assessment and Future Research Directions

Authors : Yujie Wei, Varun Kasireddy, Burcu Akinci

Published in: Advanced Computing Strategies for Engineering

Publisher: Springer International Publishing

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Abstract

With rapid developments in 3D imaging technology, as well as the evolving need in Architecture/Engineering/Construction/Facility Management (AEC/FM) industry to understand various field aspects from a 3D perspective, several technologies, such as laser scanning, camera and RGBD camera, are becoming important components of civil engineers’ and architects’ toolbox. With improvements in efficiency and reduction in operational cost, new avenues are opening in leveraging 3D imaging sensors for construction and infrastructure management. In the light of this, there is a need to assess the achievements to date, especially with respect to unique challenging use case scenarios and requirements that construction and infrastructure management domains provide, and consequently identify potential research challenges that still need to be tackled. This paper targets doing such an assessment around several challenges faced when using 3D imaging to support construction and infrastructure management. It specifically discusses to what extent these challenges have been addressed and several approaches that are used in addressing them. It also presents current 3D imaging development trends and discusses briefly some challenges that are emerging due to increased application of 3D imaging techniques to highlight future research needs in this domain.

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Metadata
Title
3D Imaging in Construction and Infrastructure Management: Technological Assessment and Future Research Directions
Authors
Yujie Wei
Varun Kasireddy
Burcu Akinci
Copyright Year
2018
Book
Advanced Computing Strategies for Engineering

Print ISBN: 978-3-319-91634-7

Electronic ISBN: 978-3-319-91635-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-91635-4_3

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