A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections

Joakim Bruslund Haurum*, Thomas B. Moeslund

*Kontaktforfatter

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Resumé

This survey presents an in-depth overview of the last 25 years of research within the field of image-based automation of Closed-Circuit Television (CCTV) and Sewer Scanner and Evaluation Technology (SSET) sewer inspection. The survey investigates both the algorithmic pipeline, and the datasets and corresponding evaluation protocols.As a result of the indepth survey, several trends within the research field are revealed, discussed, and future research directions are proposed. Based on the conducted survey, we put forth a set of three recommendations, which we believe will further improve and open the research field, aswell as make the future research more reproducible: 1) The introduction of free and public benchmark datasets, 2) Standardized evaluation metrics, and 3) Open-sourcing the associated code.
OriginalsprogEngelsk
TidsskriftAutomation in Construction
Vol/bind111
Antal sider19
ISSN0926-5805
DOI
StatusUdgivet - mar. 2020

Fingerprint

Sewers
Television
Automation
Inspection
Networks (circuits)
Pipelines

Emneord

  • Sewer Inspection
  • Computer Vision
  • Closed-Circuit Television
  • Automated Inspection
  • Sewerage Infrastructure
  • Image Processing

Citer dette

Haurum, Joakim Bruslund ; Moeslund, Thomas B. / A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections. I: Automation in Construction. 2020 ; Bind 111.
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abstract = "This survey presents an in-depth overview of the last 25 years of research within the field of image-based automation of Closed-Circuit Television (CCTV) and Sewer Scanner and Evaluation Technology (SSET) sewer inspection. The survey investigates both the algorithmic pipeline, and the datasets and corresponding evaluation protocols.As a result of the indepth survey, several trends within the research field are revealed, discussed, and future research directions are proposed. Based on the conducted survey, we put forth a set of three recommendations, which we believe will further improve and open the research field, aswell as make the future research more reproducible: 1) The introduction of free and public benchmark datasets, 2) Standardized evaluation metrics, and 3) Open-sourcing the associated code.",
keywords = "Sewer Inspection, Computer Vision, Closed-Circuit Television, Automated Inspection, Sewerage Infrastructure, Image Processing",
author = "Haurum, {Joakim Bruslund} and Moeslund, {Thomas B.}",
year = "2020",
month = "3",
doi = "10.1016/j.autcon.2019.103061",
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Haurum, JB & Moeslund, TB 2020, 'A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections', Automation in Construction, bind 111. https://doi.org/10.1016/j.autcon.2019.103061

A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections. / Haurum, Joakim Bruslund; Moeslund, Thomas B.

I: Automation in Construction, Bind 111, 03.2020.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

TY - JOUR

T1 - A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections

AU - Haurum, Joakim Bruslund

AU - Moeslund, Thomas B.

PY - 2020/3

Y1 - 2020/3

N2 - This survey presents an in-depth overview of the last 25 years of research within the field of image-based automation of Closed-Circuit Television (CCTV) and Sewer Scanner and Evaluation Technology (SSET) sewer inspection. The survey investigates both the algorithmic pipeline, and the datasets and corresponding evaluation protocols.As a result of the indepth survey, several trends within the research field are revealed, discussed, and future research directions are proposed. Based on the conducted survey, we put forth a set of three recommendations, which we believe will further improve and open the research field, aswell as make the future research more reproducible: 1) The introduction of free and public benchmark datasets, 2) Standardized evaluation metrics, and 3) Open-sourcing the associated code.

AB - This survey presents an in-depth overview of the last 25 years of research within the field of image-based automation of Closed-Circuit Television (CCTV) and Sewer Scanner and Evaluation Technology (SSET) sewer inspection. The survey investigates both the algorithmic pipeline, and the datasets and corresponding evaluation protocols.As a result of the indepth survey, several trends within the research field are revealed, discussed, and future research directions are proposed. Based on the conducted survey, we put forth a set of three recommendations, which we believe will further improve and open the research field, aswell as make the future research more reproducible: 1) The introduction of free and public benchmark datasets, 2) Standardized evaluation metrics, and 3) Open-sourcing the associated code.

KW - Sewer Inspection

KW - Computer Vision

KW - Closed-Circuit Television

KW - Automated Inspection

KW - Sewerage Infrastructure

KW - Image Processing

U2 - 10.1016/j.autcon.2019.103061

DO - 10.1016/j.autcon.2019.103061

M3 - Journal article

VL - 111

JO - Automation in Construction

JF - Automation in Construction

SN - 0926-5805

ER -

Haurum JB, Moeslund TB. A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections. Automation in Construction. 2020 mar;111. https://doi.org/10.1016/j.autcon.2019.103061

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Projekter

Autonomous Sewer Inspection Robot

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