TY - GEN
T1 - Methodologies of Audio-Visual Biometric Performance Evaluation for the H2020 SpeechXRays Project
AU - Mtibaa, Aymen
AU - Hmani, Mohamed Amine
AU - Petrovska-Delacretaz, Dijana
AU - Boudy, Jerome
AU - Hamida, Ahmed Ben
AU - Bauzou, Claude
AU - Crucianu, Iacob
AU - Markopoulos, Ioannis
AU - Spanakis, Emmanouil
AU - Nicolin, Alexandru
AU - Narr, Christian
AU - Kockmann, Marcel
AU - Perez, Javier
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - Biometric recognition is nowadays widely used in different services and applications, making the user authentication easier and more secure than the traditional authentication system. Starting from this idea, the EU SpeechXRays project H2020 developed and evaluated in real-life environments a user recognition platform based on face and voice modalities. Since the proposed biometric solution was evaluated in real-life environments where biometric data recorded was not accessible because of the General Data Protection Regulation GDPR, the ground truth of the conducted evaluation was not available. To correctly report the performance evaluation, some methodologies were proposed to detect the errors caused by the absence of ground truth. This paper describes the biometric solution provided by the project and presents the biometric performance evaluation carried out in three real-life use case pilots on more than 2 000 users.
AB - Biometric recognition is nowadays widely used in different services and applications, making the user authentication easier and more secure than the traditional authentication system. Starting from this idea, the EU SpeechXRays project H2020 developed and evaluated in real-life environments a user recognition platform based on face and voice modalities. Since the proposed biometric solution was evaluated in real-life environments where biometric data recorded was not accessible because of the General Data Protection Regulation GDPR, the ground truth of the conducted evaluation was not available. To correctly report the performance evaluation, some methodologies were proposed to detect the errors caused by the absence of ground truth. This paper describes the biometric solution provided by the project and presents the biometric performance evaluation carried out in three real-life use case pilots on more than 2 000 users.
KW - Audio-visual recognition
KW - performance evaluation
UR - https://www.scopus.com/pages/publications/85096583745
U2 - 10.1109/ATSIP49331.2020.9231680
DO - 10.1109/ATSIP49331.2020.9231680
M3 - Conference contribution
AN - SCOPUS:85096583745
T3 - 2020 International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2020
BT - 2020 International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2020
Y2 - 2 September 2020 through 5 September 2020
ER -