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Face de-identification for privacy protection

November 3 @ 4:00 am 4:00 pm CET

Café talk on “Face de-identification for privacy protection” with Ioannis Pitas (Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab).

Privacy protection is a very important issue, in the context of social media and GDPR. This lecture overviews the face de-identification problem from an engineering perceptive. In principle, face de-identification methods aim on calculating an affine or a non-linear transformation to an input facial image, so that the depicted person identity is no longer recognized by humans or automated human analysis tools. Traditional applications in the media mainly involve applying additive noise (e.g., pixilation, blurring) or reconstruction-based techniques on the facial image region, achieving sufficient de-identification performance at the expense of corroding image quality. Recently proposed deep learning-based generative methods for face de-identification promise excellent de-identification performance against automated tools while producing visually pleasing yet still not useful images for the human viewers. Finally, adversarial-based face de-identification methods optimally generate the minimum required additive noise that disables automated face detection/recognition systems, thus the de-identified images maintain maximal utility for human viewers.

Ein Bild, das Mann, Person, Schlips, Anzug enthält.

Automatisch generierte Beschreibung


Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki (AUTH), Greece. Since 1994, he has been a Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab. He served as a Visiting Professor at several Universities.

His current interests are in the areas of computer vision, machine learning, autonomous systems, intelligent digital media, image/video processing, human-centred computing, affective computing, 3D imaging and biomedical imaging. He has published over 1000 papers, contributed in 47 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 70 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 42 such projects. Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/. He is AUTH principal investigator in H2020 R&D projects Aerial Core and AI4Media. He is chair of the Autonomous Systems Initiative https://ieeeasi.signalprocessingsociety.org/. He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe). He has 31750+ citations to his work and h-index 85+ (Google Scholar).