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Marine imaging with cameras is a major method in the science, policy and public understanding of the world’s oceans. The topic is developing rapidly, driven by the technological evolution and increasing application of marine imaging in all oceans. Photos and videos are used to explore unseen ocean habitats, to motivate designation of marine conservation areas, for assessing environmental baselines and monitoring of human impacts and to communicate ocean narratives.


Information on MIW24 @ MBARI, Monterey Bay (October 2024):

The international Marine Imaging Workshops assemble around 100 scientists and engineers from different disciplines to push the boundaries of marine imaging. Biologists, ecologists, computer scientists, end-users and stakeholders discuss the methods and procedures for optimising the ways we harvest information through images. Topics cover everything from the start to finish of marine image analysis: acquisition planning, image collection, processing of images prior to annotation, still/video annotation, the future of annotation, FAIR image data management and much more.

So far, four Workshops were conducted:
  • MIW 2014 at the National Oceanography Centre Southampton
  • MIW 2017 at the GEOMAR Helmholtz Centre for Ocean Research Kiel
  • MIW 2019 at Ocean Networks Canada, Victoria
  • MIW 2022at Ifremer, Brest
To receive further information about upcoming MIWs through the mailing list, please send us an email.


The global Marine Imaging Community brings together scientists and engineers at the cutting edge of marine imaging research and technology development, along with users from regulatory agencies, consultancies and industrial partners that apply marine imaging for scientific aims, exploration, art, training or environmental monitoring.

With our multidisciplinary approach, we aim to advance the capabilities and application potential of underwater imaging methods and technology by:

  • discussing and promoting image-based research and technological improvements;
  • sharing new applications of marine imaging methods;
  • facilitating the incorporation of domain knowledge and experience from imaging stakeholders; and,
  • developing community-wide best practices for marine imaging.

Our scope includes methods and technology for all types of underwater optical imaging, including still images (photos) and moving images (video), captured by cameras on all types of imaging platforms in both pelagic and benthic environments. We address all stages of marine imaging, from survey design to camera and platform engineering to image acquisition, image processing, image manipulation through imagery annotation to FAIR image data management and applications of artificial intelligence / computer vision techniques.

We host the Marine Imaging Workshop, which welcomes participants from all marine imaging-related backgrounds and levels of experience. We develop and advertise hands on material to help marine imagers strive for better creation, use and publication of image data.

Our communication channels are a mailing list and a Slack channel. Just send us an email to be added to the mailing list or checkout to join the discussions.

Working groups

The marine imaging community keeps focus topics active between Marine Imaging Workshops through informal working groups (WGs). They act as a platform to continuously work together as a team on specific frontiers of the marine imaging research.
Working groups aim to provide open access (executive) summary reports as documents for the wider public.

WG FAIR images:

Making image data FAIR (Findable, Accessible, Interoperable and Reusable) is a major challenge. Image data is massive in size, thus complicated to handle or transfer over the Internet. Metadata standards are lacking or incomplete and standards for annotations of image data are either outdated or incompatible to the needs of marine imaging.
This WG aims to solve these challenges by developing a flexible metadata standard can incorporate core image metadata as well as information on image capture, image content up to image annotations. These standards are mainly developed by the DataHub initiative and aim at being the perfect fit to solve the needs of marine imagers without being a hassle in the daily marine imaging workflow.
Please contact tschoening [at] if you would like to participate in this working group.

Suggested WGs:

  • Automation: identifying gaps and frontiers in automation, aiming to advance the methods as well as the accessibility to them
  • Annotation: developing best-practices for image annotation, publishing them as hand-on material to create robust / benchmark image annotation data.
  • State-of-the-art: identification of relevant software (packages) that are widely used in the community that could become benchmarks. Identification of colleagues and publications related to marine imaging
  • Locating, creating and publishing benchmark data sets for the evaluation of machine learning methods - Publication of best-practices to report automated image analysis methods as well as results
Contact us at if you would like to participate in a WG, lead one of the suggested WGs or propose another topic.


Marine Imaging Reports:

iFDO (FAIR Digital Objects for image metadata)


Standard operating procedures

Developed by the MareHub working group on Images and the HMC project FDO-5DI:

Marine Sampling Field Manuals for Monitoring Australia’s Marine Waters developed by the Marine Biodiversity Hub:


Selection tool for imaging usecases

Are you trying to figure out which image analysis use case are possible with your dataset? Or are you trying to optimise your image acquisition settings for your use case? Try this tool to find the right setting and use cases.

FAIR images

Achieving FAIRness and Openness of (marine) image data requires structured and standardised metadata on the image data itself and the visual and semantic image data content. This metadata can be provided in the form of FAIR digital objects for images (iFDOs). Checkout the documentation pages that describe how iFDOs are structured and why. An iFDO is a human and machine-readable file format for an entire image set, except that it does not contain the actual image data, only references to it through persistent identifiers! Efforts are ongoing to make iFDOs available through a Python package, as a plugin to BIIGLE and QGIS.


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