Physiological Biometrics
Physiological biometrics leverages unique human biological traits for identification and authentication, aiming to improve security and user experience across various applications. Current research emphasizes enhancing accuracy and robustness, particularly addressing biases in existing models, improving liveness detection across diverse datasets, and developing privacy-preserving techniques like image distortion and cancelable biometrics. These advancements are crucial for mitigating security risks, improving the reliability of biometric systems, and ensuring ethical and responsible deployment in diverse contexts such as law enforcement, healthcare, and online security.
Papers
Combining Blockchain and Biometrics: A Survey on Technical Aspects and a First Legal Analysis
Mahdi Ghafourian, Bilgesu Sumer, Ruben Vera-Rodriguez, Julian Fierrez, Ruben Tolosana, Aythami Moralez, Els Kindt
Criminal Investigation Tracker with Suspect Prediction using Machine Learning
S. J. Dilmini, R. A. T. M. Rajapaksha, Erandika Lakmali, S. P. S. Mandula, D. D. G. Delgasdeniya, Pradeepa Bandara
OTB-morph: One-Time Biometrics via Morphing
Mahdi Ghafourian, Julian Fierrez, Ruben Vera-Rodriguez, Aythami Morales, Ignacio Serna
Unique Identification of 50,000+ Virtual Reality Users from Head & Hand Motion Data
Vivek Nair, Wenbo Guo, Justus Mattern, Rui Wang, James F. O'Brien, Louis Rosenberg, Dawn Song
Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs
Mohammad Mahdi Dehshibi, Temitayo Olugbade, Fernando Diaz-de-Maria, Nadia Bianchi-Berthouze, Ana Tajadura-Jiménez
Efficient aggregation of face embeddings for decentralized face recognition deployments (extended version)
Philipp Hofer, Michael Roland, Philipp Schwarz, René Mayrhofer