4th Edition of the ImageCLEF Coral Annotation Challenge 2022 Call for Papers

Website: https://www.imageclef.org/2022/coral


The 4th Edition of the ImageCLEF Coral Annotation Challenge 2022
The increasing use of structure-from-motion photogrammetry for
modelling large-scale environments from action cameras attached to
drones has driven the next-generation of visualisation techniques that
can be used in augmented and virtual reality headsets. It has also
created a need to have such models labelled, with objects such as
people, buildings, vehicles, terrain, etc. all essential for machine
learning techniques to automatically identify as areas of interest and
to label them appropriately. However, the complexity of the images
makes impossible for human annotators to assess the contents of images
on a large scale.

Advances in automatically annotating images for complexity and benthic
composition have been promising, and we are interested in
automatically identify areas of interest and to label them
appropriately for monitoring coral reefs. Coral reefs are in danger of
being lost within the next 30 years, and with them the ecosystems they
support. This catastrophe will not only see the extinction of many
marine species, but also create a humanitarian crisis on a global
scale for the billions of humans who rely on reef services. By
monitoring the changes and composition of coral reefs we can help
prioritise conservation efforts.

New for 2022:

Previous editions of ImageCLEFcoral in 2019 and 2020 have shown
improvements in task performance and promising results on
cross-learning between images from geographical regions. The 3rd
edition in 2021 increased the complexity of the task and size of data
available to participants through supplemental data, resulting in
lower performance than previous years. The 4th edition plans to
address these issues by targeting algorithms for geographical regions
and raising the benchmark performance. As with the 3rd edition, the
training and test data will form the complete set of images required
to form 3D reconstructions of the marine environment. This will allow
the participants to explore novel probabilistic computer vision
techniques based around image overlap and transposition of data

Challenge description

Participants will be require to annotate and localise coral reef
images by labelling the images with types of benthic substrate
together. Each image is provided with possible class
types. ImageCLEFcoral 2022 consists of two substaks:

    Coral reef image annotation and localisation: 
    Coral reef image pixel-wise parsing: 


The data for this task originates from a growing, large-scale
collection of images taken from coral reefs around the world as part
of a coral reef monitoring project with the Marine Technology Research
Unit at the University of Essex. The images partially overlap with
each other and can be used to create 3D photogrammetric models of the
marine environment.

Substrates of the same type can have very different morphologies,
coloUr variation and patterns. Some of the images contain a white line
(scientific measurement tape) that may occlude part of the entity.The
quality of the images is variable, some are blurry, and some have poor
colour balance due to the cameras being used. This is representative
of the Marine Technology Research Unit dataset and all images are
useful for data analysis. The training set used for 2022 has undergone
a significant review in order to rectify errors in classification and
polygon shape. Additionally, the 13 substrate types have been refined
to help participants understand the results of their analyses.

Important dates

    07.02.2022: development data released
    14.03.2022: test data release starts
    06.05.2021: deadline for submitting the participants runs
    27.05.2021: deadline for submission of working notes papers by the participants
    5-8.09.2021: CLEF 2022, Bologna, Italy


Participant Registration



Organizing Committee

    Jon Chamberlain ,University of Essex, UK
    Antonio Campello ,Wellcome Trust, UK
    Adrian Clark ,University of Essex, UK
    Alba García Seco de Herrera ,University of Essex, UK


For more details and updates, please visit the task website at: 

And join our mailing list: https://groups.google.com/d/forum/imageclefcoral