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Probabilistic Bayesian framework for infrared face recognition


Moulay Akhloufi and Abdel Hakim Bendada

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Abstract - Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

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Bibtex:

@inproceedings{Akhloufi791,
    author    = { Moulay Akhloufi and Abdel Hakim Bendada },
    title     = { Probabilistic Bayesian framework for infrared face recognition },
    booktitle = { International Conference on Machine Vision, Image Processing, and Pattern Analysis (MVIPPA 2009) },
    volume    = { 60 },
    series    = { Proceedings of WASET },
    pages     = { 66-70 },
    address   = { Bangkok, Thailand },
    year      = { 2009 },
    month     = { December },
    journal   = { International Conference on Machine Vision, Image Processing, and Pattern Analysis (MVIPPA 2009) },
    ISBN      = { ISSN: 2070-3724 },
    keywords  = { Face recognition, biometrics, probabilistic image processing, infrared imaging. },
    language  = { English },
    web       = { http://www.waset.org/journals/waset/v60/v60-10.pdf }
}

Last modification: Feb 21 2010 3:05PM by akhloufi

     
   
   

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