Abstract
In this paper, we present a novel algorithm for 3D face recognition that is robust to the rotations and translations of the face models. Based on the Iterative Closest Point algorithm, a template based registration strategy is proposed for data normalization. Back-Propagation neural networks are then constructed to perform recognition tasks. The proposed algorithm is general purpose and can be applied for common 3D object recognitions. Experimental results illustrate that the algorithm is effective and robust.
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© 2005 Springer-Verlag Berlin Heidelberg
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Niu, B., Shiu, S.C.K., Pal, S.K. (2005). A Novel 3D Face Recognition Algorithm Using Template Based Registration Strategy and Artificial Neural Networks. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_46
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DOI: https://doi.org/10.1007/11590316_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30506-4
Online ISBN: 978-3-540-32420-1
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