In this paper, we propose a novel shape representation we call directional histogram model (DHM). It captures the shape variation of an object and is invariant to scaling and rigid transforms. The DHM is computed by first extracting a directional distribution of thickness histogram signatures, which are translation invariant. We show how the extraction of the thickness histogram distribution can be accelerated using conventional graphics hardware. Orientation invariance is achieved by computing the spherical harmonic transform of this distribution. Extensive experiments show that the DHM is capable of high discrimination power and is robust to noise.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Directional histogram model for three-dimensional shape similarity


    Contributors:
    Xinguo Liu, (author) / Su, R. (author) / Sing Bing Kang, (author) / Heung-Yeung, Shum. (author)


    Publication date :

    2003-01-01


    Size :

    530154 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Directional Histogram Model for Three-Dimensional Shape Similarity

    Liu, X. / Sun, R. / Kang, S. et al. | British Library Conference Proceedings | 2003


    Histogram similarity measure using variable bin size distance

    Ma, Y. / Gu, X. / Wang, Y. | British Library Online Contents | 2010


    Shape gradients for histogram segmentation using active contours

    Jehan-Besson, / Barlaud, / Aubert, et al. | IEEE | 2003


    THREE-DIMENSIONAL DIRECTIONAL OPTICAL ANTENNA

    TANAKA SHINICHI / ISHIHARA HIROSHI | European Patent Office | 2019

    Free access

    Shape Gradients for Histogram Segmentation Using Active Contours

    Jehan-Besson, S. / Barland, M. / Aubert, G. et al. | British Library Conference Proceedings | 2003