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Although modern machine learning has the potential to greatly speed up the interpretation of imagery, the varied nature of the seabed and limited availability of expert annotations form barriers to its widespread use in seafloor mapping applications. This motivates research into unsupervised methods that function without large databases of human annotations. This paper develops an unsupervised feature...
Visual maps of the seafloor can provide objective information to characterize benthic ecosystems and survey the distribution of mineral deposits on spatial scales that cannot be otherwise assessed. This paper proposes a three‐dimensional mapping method based on light sectioning that enables the simultaneous capture of both structure and color from the images of a single camera. The advantages of the...
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