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    3D face recognition based on machine learning

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    Publication date
    2008
    Author
    Qatawneh, S.
    Ipson, Stanley S.
    Qahwaji, Rami S.R.
    Ugail, Hassan
    Keyword
    3D face recognition
    CCNN
    ABS images
    Feature extraction
    Machine learning
    Rights
    © 2008 IASTED and ACTA Press. Reproduced in accordance with the publisher's self-archiving policy
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    3D facial data has a great potential for overcoming the problems of illumination and pose variation in face recognition. In this paper, we present a 3D facial system based on the machine learning. We used landmarks for feature extraction and Cascade Correlation neural network to make the final decision. Experiments are presented using 3D face images from the Face Recognition Grand Challenge database version 2.0. For CCNN using Jack-knife evaluation, an accuracy of 100% has been achieved for 7 faces with different expression, with 100% for both of specificity and sensitivity.
    URI
    http://hdl.handle.net/10454/2433
    Version
    Accepted Manuscript
    Citation
    Qatawneh, S., Ipson, S., Qahwaji, R. S. R. and Ugail, H. (2008). 3D face recognition based on machine learning. In: Villanueva, J.J. (ed.) Proceedings of the Eighth IASTED International Conference on Visualization, Imaging and Image Processing (VIIP 2008) September 1-3, 2008, Palma de Mallorca, Spain. Calgary: Acta Press. pp. 362-366.
    Link to publisher’s version
    http://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=494#pages
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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