A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Use of depth and colour eigenfaces for face recognition
Pattern Recognition Letters
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Face Modeling and Recognition in 3-D
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
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
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
Rank-Based decision fusion for 3d shape-based face recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Applying parallel design techniques to template matching with GPUs
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
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This paper proposes a novel approach to both registration and recognition of face in three dimensions. The presented method is based on normal map metric to perform either the alignment of captured face to a reference template or the comparison between any two faces in a gallery. As the metric involved is highly suited to be computed via vector processor, we propose an implementation of the whole framework on last generation graphics boards, to exploit the potential of GPUs applied to large scale biometric identification applications. This work shows how the use of affordable consumer grade hardware could allow ultra rapid comparison between face descriptors through their highly specialized architecture. The approach also addresses facial expression changes by means of a subject specific weighting masks. We include preliminary results of experiments conducted on a proprietary gallery and on a subset of FRGC database.