TLS-Point Clouding-3D Shape Deflection Monitoring

Gichun Cha; Byungjoon Yu; Sehwan Park; Seunghee Park

doi:10.1007/978-3-030-17795-9_36

TLS-Point Clouding-3D Shape Deflection Monitoring

Gichun Cha
, Byungjoon Yu
, Sehwan Park
, Seunghee Park

Department of Civil, Architectural Engineering and Landscape Architecture

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

As high-rise buildings and aging structures increase, researches are underway to effectively inspect structures and prevent accidents in Korea. The structure cannot maintain its original shape due to natural disasters and loads, and deformation occurs. The accidents caused by the deformation of the structure have become a common news in the surroundings. Therefore, this study proposes a noncontact shape management monitoring method that can check structures and detect deformation.

Original language	English
Title of host publication	Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC
Editors	Kohei Arai, Supriya Kapoor
Publisher	Springer Verlag
Pages	497-502
Number of pages	6
ISBN (Print)	9783030177942
DOIs	https://doi.org/10.1007/978-3-030-17795-9_36
State	Published - 2020
Event	Computer Vision Conference, CVC 2019 - Las Vegas, United States Duration: 25 Apr 2019 → 26 Apr 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	943
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Computer Vision Conference, CVC 2019
Country/Territory	United States
City	Las Vegas
Period	25/04/19 → 26/04/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Deflection Monitoring
ICP algorithm
Point cloud
Terrestrial Laser Scanning

Access to Document

10.1007/978-3-030-17795-9_36

Cite this

@inproceedings{623819afefde4614a71119cf0afdd007,

title = "TLS-Point Clouding-3D Shape Deflection Monitoring",

abstract = "As high-rise buildings and aging structures increase, researches are underway to effectively inspect structures and prevent accidents in Korea. The structure cannot maintain its original shape due to natural disasters and loads, and deformation occurs. The accidents caused by the deformation of the structure have become a common news in the surroundings. Therefore, this study proposes a noncontact shape management monitoring method that can check structures and detect deformation.",

keywords = "Deflection Monitoring, ICP algorithm, Point cloud, Terrestrial Laser Scanning",

author = "Gichun Cha and Byungjoon Yu and Sehwan Park and Seunghee Park",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; Computer Vision Conference, CVC 2019 ; Conference date: 25-04-2019 Through 26-04-2019",

year = "2020",

doi = "10.1007/978-3-030-17795-9\_36",

language = "English",

isbn = "9783030177942",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "497--502",

editor = "Kohei Arai and Supriya Kapoor",

booktitle = "Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC",

}

Cha, G, Yu, B, Park, S & Park, S 2020, TLS-Point Clouding-3D Shape Deflection Monitoring. in K Arai & S Kapoor (eds), Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. Advances in Intelligent Systems and Computing, vol. 943, Springer Verlag, pp. 497-502, Computer Vision Conference, CVC 2019, Las Vegas, United States, 25/04/19. https://doi.org/10.1007/978-3-030-17795-9_36

TLS-Point Clouding-3D Shape Deflection Monitoring. / Cha, Gichun; Yu, Byungjoon; Park, Sehwan et al.
Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. ed. / Kohei Arai; Supriya Kapoor. Springer Verlag, 2020. p. 497-502 (Advances in Intelligent Systems and Computing; Vol. 943).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - TLS-Point Clouding-3D Shape Deflection Monitoring

AU - Cha, Gichun

AU - Yu, Byungjoon

AU - Park, Sehwan

AU - Park, Seunghee

PY - 2020

Y1 - 2020

N2 - As high-rise buildings and aging structures increase, researches are underway to effectively inspect structures and prevent accidents in Korea. The structure cannot maintain its original shape due to natural disasters and loads, and deformation occurs. The accidents caused by the deformation of the structure have become a common news in the surroundings. Therefore, this study proposes a noncontact shape management monitoring method that can check structures and detect deformation.

AB - As high-rise buildings and aging structures increase, researches are underway to effectively inspect structures and prevent accidents in Korea. The structure cannot maintain its original shape due to natural disasters and loads, and deformation occurs. The accidents caused by the deformation of the structure have become a common news in the surroundings. Therefore, this study proposes a noncontact shape management monitoring method that can check structures and detect deformation.

KW - Deflection Monitoring

KW - ICP algorithm

KW - Point cloud

KW - Terrestrial Laser Scanning

UR - https://www.scopus.com/pages/publications/85065473047

U2 - 10.1007/978-3-030-17795-9_36

DO - 10.1007/978-3-030-17795-9_36

M3 - Conference contribution

AN - SCOPUS:85065473047

SN - 9783030177942

T3 - Advances in Intelligent Systems and Computing

SP - 497

EP - 502

BT - Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC

A2 - Arai, Kohei

A2 - Kapoor, Supriya

PB - Springer Verlag

T2 - Computer Vision Conference, CVC 2019

Y2 - 25 April 2019 through 26 April 2019

ER -

TLS-Point Clouding-3D Shape Deflection Monitoring

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this