Deep Learning for Wearable Biometrics
Wearable devices are rapidly becoming widespread, to an extent that they have been often mentioned as the next big thing in personal computing after mobile devices. This is due to the several capabilities these devices can offer, exploited for applications ranging from monitoring fitness or health-related parameters to controlling virtual reality avatars.
In addition to their existing functionalities, wearable devices intrinsically offer the possibilities of being exploited for biometric recognition purposes. In fact, the physiological characteristics they can capture typically possess unique properties that could enable the identification of legitimate subjects and the detection of unauthorized usage.
This lecture will delve into the latest advancements in this domain, examining the current state of the art along with associated unresolved issues. More specifically, the techniques relying on deep learning approaches that can be employed to implement reliable and efficient biometric recognition systems based on wearable devices will be illustrated. Systems leveraging traits such as photoplethysmogram (PPG), electrodermal activity (EDA), and seismocardiogram (SCG) will be explored as illustrative examples.
Date and Time
Location
Hosts
Registration
- Date: 11 Jul 2024
- Time: 09:00 AM UTC to 11:00 AM UTC
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- ESEO Dijon Campus
- 11 rue Sully 21
- Dijon, Unknown
- France
- Starts 26 June 2024 11:00 PM UTC
- Ends 10 July 2024 11:00 PM UTC
- No Admission Charge
Speakers
Emanuele Maiorana
Biography:
Emanuele Maiorana received the Ph.D. degree in biomedical, electromagnetism, and telecommunication engineering with European Doctorate Label from Roma Tre University, Rome, Italy, in 2009. He is currently a tenure track Assistant Professor with the Section of Applied Electronics, Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy. His research interests are in the area of digital signal and image processing, with specific emphasis on biometric recognition. He is an Associate Editor of the IEEE Transactions on Information Forensics and Security since 2020. He is the recipient of the Lockheed Martin Best Paper Award for the Poster Track at the IEEE Biometric Symposium 2007, the Honeywell Student Best Paper Award at the IEEE Biometrics: Theory, Applications and Systems conference 2008, and the Best Paper Award at the International Conference on Pattern Recognition Applications and Methods (ICPRAM). He was the General Chair of the IEEE International Workshop on Biometrics and Forensics (IWBF) 2021, and he is the General Chair of the IEEE International Workshop on Information Forensics and Security (WIFS) 2024.