Exploring Transformers for Behavioural Biometrics: A Case Study in Gait Recognition

no code implementations • 3 Jun 2022 • Paula Delgado-Santos, Ruben Tolosana, Richard Guest, Farzin Deravi, Ruben Vera-Rodriguez

Biometrics on mobile devices has attracted a lot of attention in recent years as it is considered a user-friendly authentication method.

Gait Recognition

Adaptive Template Enhancement for Improved Person Recognition using Small Datasets

no code implementations • 3 Jan 2022 • Su Yang, Sanaul Hoque, Farzin Deravi

A novel instance-based method for the classification of electroencephalography (EEG) signals is presented and evaluated in this paper.

Classification EEG +1

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

no code implementations • 17 Nov 2021 • Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R Freire, Joaquin Gonzalez-Rodriguez, Carmen Garcia-Mateo, Jose-Luis Alba-Castro, Elisardo Gonzalez-Agulla, Enrique Otero-Muras, Sonia Garcia-Salicetti, Lorene Allano, Bao Ly-Van, Bernadette Dorizzi, Josef Kittler, Thirimachos Bourlai, Norman Poh, Farzin Deravi, Ming NR Ng, Michael Fairhurst, Jean Hennebert, Andreas Humm, Massimo Tistarelli, Linda Brodo, Jonas Richiardi, Andrezj Drygajlo, Harald Ganster, Federico M Sukno, Sri-Kaushik Pavani, Alejandro Frangi, Lale Akarun, Arman Savran

It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware.

GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learning

no code implementations • 8 Oct 2021 • Paula Delgado-Santos, Ruben Tolosana, Richard Guest, Ruben Vera, Farzin Deravi, Aythami Morales

This study proposes GaitPrivacyON, a novel mobile gait biometrics verification approach that provides accurate authentication results while preserving the sensitive information of the subject.

Privacy Preserving