Deep neural networks for analysis of fisheries surveillance video and automated monitoring of fish discards

Geoffrey French, Michal Mackiewicz, Mark Fisher, Helen Holah, Rachel Kilburn, Neil Campbell, Coby Needle

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
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Abstract

We report on the development of a computer vision system that analyses video from CCTV systems installed on fishing trawlers for the purpose of monitoring and quantifying discarded fish catch. Our system is designed to operate in spite of the challenging computer vision problem posed by conditions on-board fishing trawlers. We describe the approaches developed for isolating and segmenting individual fish and for species classification. We present an analysis of the variability of manual species identification performed by expert human observers and contrast the performance of our species classifier against this benchmark. We also quantify the effect of the domain gap on the performance of modern deep neural network-based computer vision systems.
Original languageEnglish
Pages (from-to)1340–1353
Number of pages14
JournalICES Journal of Marine Science
Volume77
Issue number4
Early online date1 Aug 2019
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Computer vision and CCTV
  • Deep learning

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