We propose a discriminative feature selection method utilizing support vector machines for the challenging task of multiview face recognition. According to the statistical relationship between the two tasks, feature selection and multiclass classification, we integrate the two tasks into a single consistent framework and effectively realize the goal of discriminative feature selection. The classification process can be made faster without degrading the generalization performance through this discriminative feature selection method. On the UMIST multiview face database, our experiments show that this discriminative feature selection method can speed up the multiview face recognition process without degrading the correct rate and outperform the traditional kernel subspace methods.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fast recognition of multi-view faces with feature selection


    Contributors:


    Publication date :

    2005-01-01


    Size :

    203642 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Fast Recognition of Multi-view Faces with Feature Selection

    Fan, Z.-G. / Lu, B.-L. / IEEE | British Library Conference Proceedings | 2005


    Multi-view face recognition from single RGBD models of the faces

    Kim, Donghun / Comandur, Bharath / Medeiros, Henry et al. | British Library Online Contents | 2017


    Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection

    Zhou, X. / Comaniciu, D. / Krishnan, A. et al. | British Library Conference Proceedings | 2003


    Fast recognition of multiple faces using MCM

    Manoj Seshadrinathan, / Ben-Arie, J. | IEEE | 2003


    Fast Recognition of Multiple Faces using MCM

    Seshadrinathan, M. / Ben-Arie, J. / IEEE et al. | British Library Conference Proceedings | 2003