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FathomNet: A global image database for enabling artificial intelligence in the ocean
Katija, K.; Orenstein, E.; Schlining, B.; Lundsten, L.; Barnard, K.; Sainz, G.; Boulais, O.; Cromwell, M.; Butler, E.; Woodward, B.; Bell, K.L.C. (2022). FathomNet: A global image database for enabling artificial intelligence in the ocean. NPG Scientific Reports 12(1): 15914. https://dx.doi.org/10.1038/s41598-022-19939-2
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322; e-ISSN 2045-2322, more
Peer reviewed article  

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Keyword
    Marine/Coastal

Authors  Top 
  • Katija, K.
  • Orenstein, E.
  • Schlining, B.
  • Lundsten, L.
  • Barnard, K.
  • Sainz, G.
  • Boulais, O.
  • Cromwell, M.
  • Butler, E.
  • Woodward, B.
  • Bell, K.L.C.

Abstract
    The ocean is experiencing unprecedented rapid change, and visually monitoring marine biota at the spatiotemporal scales needed for responsible stewardship is a formidable task. As baselines are sought by the research community, the volume and rate of this required data collection rapidly outpaces our abilities to process and analyze them. Recent advances in machine learning enables fast, sophisticated analysis of visual data, but have had limited success in the ocean due to lack of data standardization, insufficient formatting, and demand for large, labeled datasets. To address this need, we built FathomNet, an open-source image database that standardizes and aggregates expertly curated labeled data. FathomNet has been seeded with existing iconic and non-iconic imagery of marine animals, underwater equipment, debris, and other concepts, and allows for future contributions from distributed data sources. We demonstrate how FathomNet data can be used to train and deploy models on other institutional video to reduce annotation effort, and enable automated tracking of underwater concepts when integrated with robotic vehicles. As FathomNet continues to grow and incorporate more labeled data from the community, we can accelerate the processing of visual data to achieve a healthy and sustainable global ocean.

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