Use of depth and colour eigenfaces for face recognition
Pattern Recognition Letters
Face Modeling and Recognition in 3-D
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Deformation Analysis for 3D Face Matching
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Adaptive Rigid Multi-region Selection for Handling Expression Variation in 3D Face Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
3D Face Recognition using Mapped Depth Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Evaluation of automatic 4D face recognition using surface and texture registration
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Hi-index | 0.00 |
Face recognition represents a challenging research topic which has been investigated by means of many techniques operating either in 2D or 3D, and, more recently, even through multi-modal approaches. Whatever the methodology used to compare any two faces, the main concern has been on recognition accuracy, often disregarding the efficiency issue which may be crucial in a large scale one-to-many recognition application. This paper presents a Graphic Processing Unit (GPU) assisted face recognition method, operating on 4D data (geometry + texture). It exploits augmented normal map, a 32 bit deep color bitmap, as face descriptor, allowing ultra fast face comparison through the specialized hardware (pixel shaders) available in almost any recently designed PC graphic boards. The proposed approach addresses facial expression changes and presence of beard by means of two (subject specific) filtering masks. We include preliminary experimental results on a large gallery of faces.