AI-Cafe presents: Face de-identification for privacy protection
Prof. 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 at calculating an affine or a non-linear transformation to an input facial image, so that the depicted person's 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 to 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.
Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and Ph.D. 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-centered computing, affective computing, 3D imaging and biomedical imaging.
He has published over 920 papers, contributed to 45 books in his areas of interest and edited or (co-)authored another 11 books. He has also been a member of the program committee of many scientific conferences and workshops. In the past, he served as Associate Editor or co-Editor of 13 international journals and General or Technical Chair of 5 international conferences. He delivered 98 keynote/invited speeches worldwide. He co-organized 33 conferences and participated in technical committees of 291 conferences. He participated in 71 R&D projects, primarily funded by the European Union and is/was principal investigator in 43 such projects. Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: .
He is AUTH principal investigator in H2020 R&D projects Aerial Core and AI4Media. He was chair and initiator of the Autonomous Systems Initiative. He is chair of the International AI Doctoral Academy (AIDA) and is PI in Horizon2020 EU-funded R&D projects AI4Media (1 of the 4 AI flagship projects in Europe) and AerialCore. He has 34400+ citations to his work and an h-index 87+.