Depth information is one of the most important factors for the recognition of a digital face image. Range images are very useful, when comparing one face with other faces, because of implicating depth information. As the processing for the whole face produces a lot of calculations and data, face images can be represented in terms of a vector of feature descriptors for a local area. In this paper, depth areas of a 3 dimensional (3D) face image were extracted by the contour line from some depth value. These were resampled and stored in consecutive location in feature vector using multiple feature method. A comparison between two faces was made based on their distance in the feature space, using Euclidian distance. This paper reduced the amount of index data in the database and used fewer feature vectors than other methods. The proposed algorithm can be highly recognized for using local depth information and less feature vectors on the face.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    3D face recognition using multiple features for local depth information


    Contributors:
    Lee, Y. (author) / Yi, T. (author)


    Publication date :

    2003-01-01


    Size :

    335889 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    3D Face Recognition using Multiple Features for Local Depth Information

    Lee, Y. / Yi, T. / IEEE et al. | British Library Conference Proceedings | 2003


    Robust local features for remote face recognition

    Chen, Jie / Patel, Vishal M. / Liu, Li et al. | British Library Online Contents | 2017


    Face recognition fusing global and local features

    Yu, W.-w. / Teng, X.-l. / Liu, C.-q. | British Library Online Contents | 2006


    3D Face Recognition using Mapped Depth Images

    Gang Pan, / Shi Han, / Zhaohui Wu, et al. | IEEE | 2005