survey

A Survey on Underwater Computer Vision

Authors:

Salma P. González-Sabbagh,

Antonio Robles-KellyAuthors Info & Claims

ACM Computing Surveys, Volume 55, Issue 13s

Article No.: 268, Pages 1 - 39

https://doi.org/10.1145/3578516

Published: 13 July 2023 Publication History

Abstract

Underwater computer vision has attracted increasing attention in the research community due to the recent advances in underwater platforms such as of rovers, gliders, autonomous underwater vehicles (AUVs), and the like, that now make possible the acquisition of vast amounts of imagery and video for applications such as biodiversity assessment, environmental monitoring, and search and rescue. Despite growing interest, underwater computer vision is still a relatively under-researched area, where the attention in the literature has been paid to the use of computer vision techniques for image restoration and reconstruction, where image formation models and image processing methods are used to recover colour corrected or enhanced images. This is due to the notion that these methods can be used to achieve photometric invariants to perform higher-level vision tasks such as shape recovery and recognition under the challenging and widely varying imaging conditions that apply to underwater scenes. In this paper, we review underwater computer vision techniques for image reconstruction, restoration, recognition, depth, and shape recovery. Further, we review current applications such as biodiversity assessment, management and protection, infrastructure inspection and AUVs navigation, amongst others. We also delve upon the current trends in the field and examine the challenges and opportunities in the area.

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Index Terms

A Survey on Underwater Computer Vision
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding

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ACM Computing Surveys Volume 55, Issue 13s

December 2023

1367 pages

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EISSN:1557-7341

DOI:10.1145/3606252

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Published: 13 July 2023

Online AM: 02 January 2023

Accepted: 12 December 2022

Revised: 26 October 2022

Received: 09 November 2021

Published in CSUR Volume 55, Issue 13s

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https://doi.org/10.1364/OE.527645
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