This paper presents a 3D facial recognition algorithm based on the Hausdorff distance metric. The standard 3D formulation of the Hausdorff matching algorithm has been modified to operate on a 2D range image, enabling a reduction in computation from O(N2) to O(N) without large storage requirements. The Hausdorff distance is known for its robustness to data outliers and inconsistent data between two data sets, making it a suitable choice for dealing with the inherent problems in many 3D datasets due to sensor noise and object self-occlusion. For optimal performance, the algorithm assumes a good initial alignment between probe and template datasets. However, to minimize the error between two faces, the alignment can be iteratively refined. Results from the algorithm are presented using 3D face images from the Face Recognition Grand Challenge database version 1.0.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A 2D Range Hausdorff Approach for 3D Face Recognition


    Contributors:
    Russ, T.D. (author) / Koch, M.W. (author) / Little, C.Q. (author)


    Publication date :

    2005-01-01


    Size :

    382928 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Face Recognition from 3D Face Profiles Using the Hausdorff Distance

    Lee, Y. / Park, K. / Shim, J. et al. | British Library Online Contents | 2003


    Robust face recognition from 2D and 3D images using structural Hausdorff distance

    Wang, Y. / Chua, C. S. | British Library Online Contents | 2006


    New star pattern recognition approach based on Hausdorff distance

    Guangjun, W. / Jiancheng, F. | British Library Online Contents | 2005



    A novel weighted Hausdorff distance for face localization

    Tan, H. / Zhang, Y. J. | British Library Online Contents | 2006