ImageCLEFcoral task: Coral reef image annotation and localisation

This paper presents an overview of the ImageCLEFcoral 2022 task that was organised as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2022. The task addresses the problem of automatically segmenting and labelling a collection of underwater images that can be used in combination to create 3D models for the monitoring of coral reefs. The training data set contains images from four Worldwide geographical locations and the test data set contains images from only one of these locations. Therefore the participants could train on a subset of geographically similar images, which has been shown in previous editions of this task to be beneficial to performance. These images are grouped into image sets that can be used to create a 3D model of the environment using photogrammetry. The training dataset contained 1,374 images and 31,517 polygon objects. The test dataset comprises 200 images and 6,319 polygon objects. 6 teams registered to the ImageCLEFcoral 2022 task, of which 2 teams submitted 11 runs. Participants’ entries showed that although automatic annotation of benthic substrates was possible, improving on the baselines set in previous years will be difficult.