We describe a framework aimed at performing face- based biometric user authentication for Web resources through client-server secured sessions. A novel front end for face video se- quences processing is developed in which face detection and shot selection are performed at the client side while statistical multishot pose-corrected face verification is performed at the server side. We explain all the image processing steps, from acquisition through de- cision, paying special attention to a PDM-based pose correction subsystem and a GMM-based sequence decision test. The pose correction relies on projecting a face-shape mesh onto the set of PDM eigenvectors and back-projecting it after changing the coeffi- cients associated with pose variation. The aligned texture features compose the observation vectors ready to be plugged into a GMM- based likelihood ratio for statistical decision. The pose correction strategy has been previously validated over the XM2VTS and CMU- PIE data sets, the GMM-based video sequence decision test has been compared to other video-based systems using the BANCA data set, and the complete proposed system has been tested on a new video data set from the European Network of Excellence
['José Luis Alba-Castro', 'Daniel González-Jiménez', 'Enrique Argones-Rúa', 'Elisardo González-Agulla', 'Enrique Otero-Muras', 'Carmen Garcia-Mateo']
Pose-corrected face processing on video sequences for webcam-based remote biometric authentication