Fast and efficient 3D face recognition using wavelet networks

Authors:
Salwa Said;Boulbaba Ben Amor;Mourad Zaied;Chokri Ben Amar;Mohamed Daoudi
Affiliations:
National Engineering School of Sfax, REGIM, DGRST, University of Sfax, Tunisia and Institut TELECOM and Telecom Lille 1, LIFL, UMR, USTL, CNRS, France;Institut TELECOM and Telecom Lille 1, LIFL, UMR, USTL, CNRS, France;National Engineering School of Sfax, REGIM, DGRST, University of Sfax, Tunisia;National Engineering School of Sfax, REGIM, DGRST, University of Sfax, Tunisia;Institut TELECOM and Telecom Lille 1, LIFL, UMR, USTL, CNRS, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

3D shape of face has recently emerged as a major research in face biometrics. However, while it is reputed to be relatively invariant to lighting conditions and pose, one still needs to cope with facial expression variations for a reliable face recognition solution and running time of the matching algorithms for fast identification software. We present in this paper our solutions to overcome these limitations. We propose a new method of 3D facial recognition based on wavelet networks. Firstly, depth image is preprocessed in order to crop the useful area of the face image. Secondly, a compact and representative biometric signature is produced by means of wavelet networks. Finally, the matching of two faces is made by computing Euclidean distance between their two corresponding signatures. To show the efficiency and accuracy of our approach, a subset taken from FRGC v2 dataset is used to made evaluations.