March 29th, 2022 
Daniela Lopez de Luise Website: https://www.imageclef.org/2022/coral
*** CALL FOR PARTICIPATION ***
The 4th Edition of the ImageCLEF Coral Annotation Challenge 2022
Data
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 points.
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: https://www.aicrowd.com/challenges/imageclef-2022-coral-annotation-and-l…
- Coral reef image pixel-wise parsing: https://www.aicrowd.com/challenges/imageclef-2022-coral-pixel-wise-parsing
Data
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
- 06.05.2022: 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
- Jon Chamberlain <jchamb(at)essex.ac.uk>,University of Essex, UK
- Antonio Campello <a.campello(at)wellcome.ac.uk>,Wellcome Trust, UK
- Adrian Clark <alien(at)essex.ac.uk>,University of Essex, UK
- Alba García Seco de Herrera <alba.garcia(at)essex.ac.uk>,University of Essex, UK
For more details and updates, please visit the task website at: https://www.imageclef.org/2022/coral
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