Investigating the boosting framework for face recognition

B.J. Boom, R.T.A. van Rootseler

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    The boosting framework has shown good performance in face recognition. By combining a set of features with Adaboost, a similarity function is developed which determines if a pair of face images belongs to the same person or not. Recently, many features have been used in combination with Adaboost, achieving good results on the FERET database. In this paper we compare the results of several features on the same database and discuss our solutions on some of the open issues in this method. We compare the boosting framework with some standard algorithms and test the boosting algorithm under difficult circumstances, like illumination and registration noise.
    Original languageUndefined
    Title of host publicationProceedings of the 28th Symposium on Information Theory in the Benelux
    EditorsRaymond N.J. Veldhuis, R.N.J. Veldhuis, H.S. Cronie
    Place of PublicationEindhoven
    PublisherWerkgemeenschap voro Informatie- en Communicatietechniek
    Number of pages8
    ISBN (Print)978-90-365-2509-1
    Publication statusPublished - 24 May 2007
    Event28th Symposium on Information Theory in the Benelux 2007 - Best Western Dish Hotel, Enschede, Netherlands
    Duration: 24 May 200725 May 2007
    Conference number: 28

    Publication series

    PublisherWerkgemeenschap voor Informatie- en Communicatietechniek


    Conference28th Symposium on Information Theory in the Benelux 2007


    • SCS-Safety
    • METIS-241829
    • EWI-10852
    • IR-64276

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