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Overview of the ImageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications

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Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13390))

Abstract

This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of the Conference and Labs of the Evaluation Forum – CLEF Labs 2022. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2022, the 20th edition of ImageCLEF runs four main tasks: (i) a medical task that groups two previous tasks, i.e., caption analysis and tuberculosis prediction, (ii) a social media aware task on estimating potential real-life effects of online image sharing, (iii) a nature coral task about segmenting and labeling collections of coral reef images, and (iv) a new fusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression). The benchmark campaign received the participation of over 25 groups submitting more than 258 runs.

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Notes

  1. 1.

    http://www.imageclef.org/.

  2. 2.

    https://www.aicrowd.com/.

  3. 3.

    https://scholar.google.com/.

  4. 4.

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

  5. 5.

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

  6. 6.

    https://www.aicrowd.com/.

  7. 7.

    https://www.ncbi.nlm.nih.gov/pmc/tools/openftlist/.

  8. 8.

    http://host.robots.ox.ac.uk/pascal/VOC/.

  9. 9.

    https://www.ncei.noaa.gov/.

  10. 10.

    https://coralnet.ucsd.edu/.

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Acknowledgements

The ImageCLEFaware and ImageCLEFfusion tasks were supported under the H2020 AI4Media “A European Excellence Centre for Media, Society and Democracy” project, contract \(\#951911\). The work of Louise Bloch and Raphael Brüngel was partially funded by a PhD grant from the University of Applied Sciences and Arts Dortmund (FH Dortmund), Germany. The work of Ahmad Idrissi-Yaghir and Henning Schäfer was funded by a PhD grant from the DFG Research Training Group 2535 Knowledge- and data-based personalisation of medicine at the point of care (WisPerMed).

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Authors and Affiliations

  1. Politehnica University of Bucharest, Bucharest, Romania

    Bogdan Ionescu, Liviu-Daniel Ştefan, Mihai Gabriel Constantin & Mihai Dogariu

  2. University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland

    Henning Müller

  3. University of La Rochelle, La Rochelle, France

    Renaud Péteri

  4. University of Applied Sciences and Arts Dortmund, Dortmund, Germany

    Johannes Rückert, Christoph M. Friedrich, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir & Henning Schäfer

  5. Microsoft, Redmond, WA, USA

    Asma Ben Abacha

  6. University of Essex, Colchester, UK

    Alba G. Seco de Herrera, Jon Chamberlain & Adrian Clark

  7. Institute for Informatics, Minsk, Belarus

    Serge Kozlovski & Vassili Kovalev

  8. University of Warwick, Coventry, UK

    Yashin Dicente Cid

  9. Université Paris-Saclay, CEA, LIST, 91120, Palaiseau, France

    Adrian Popescu, Jérôme Deshayes-Chossart & Hugo Schindler

  10. Wellcome Trust, London, UK

    Antonio Campello

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  1. Bogdan Ionescu
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Correspondence to Bogdan Ionescu .

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Editors and Affiliations

  1. University of Bologna, Forlì, Italy

    Alberto Barrón-Cedeño

  2. University of Padua, Padova, Italy

    Giovanni Da San Martino

  3. University of Bologna, Bologna, Italy

    Mirko Degli Esposti

  4. Instituto di Scienza e Tecnologie dell' Informazione “Alessandro Faedo”, Pisa, Italy

    Fabrizio Sebastiani

  5. University of Glasgow, Glasgow, UK

    Craig Macdonald

  6. University Milano-Bicocca, Milan, Italy

    Gabriella Pasi

  7. TU Wien, Vienna, Austria

    Allan Hanbury

  8. Leipzig University, Leipzig, Germany

    Martin Potthast

  9. University of Padua, Padova, Italy

    Guglielmo Faggioli

  10. University of Padua, Padova, Italy

    Nicola Ferro

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Ionescu, B. et al. (2022). Overview of the ImageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications. In: Barrón-Cedeño, A., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2022. Lecture Notes in Computer Science, vol 13390. Springer, Cham. https://doi.org/10.1007/978-3-031-13643-6_31

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