Existing approaches to characterizing image texture usually rely on computing a local response to a bank of correlation filters, such as derivatives of a Gaussian, in one image. Recently, significant progress has been made in characterizing a single texture under varying viewpoint and illumination conditions, leading to the bi-directional texture function that describes the smooth variation of filter responses as a function of viewpoint and illumination. However, this technique does not attempt to exploit the redundancy of multiple images; each image is treated independently. In video data, close correspondences between frames enable a new form of texture analysis that incorporates local 3D structure as well as intensity variation. We exploit this relationship to characterize texture with significant 3D structure, such as foliage, across a range of viewpoints. This paper presents a general overview of these ideas and preliminary results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Using video for recovering texture


    Beteiligte:
    Hoogs, A. (Autor:in) / Kaucic, R. (Autor:in) / Collins, R. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    1103853 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Using Video for Recovering Texture

    Hoogs, A. / Kaucic, R. / Collins, R. | British Library Conference Proceedings | 2001


    Recovering Object Surfaces from Viewed Changes in Surface Texture Patterns

    Belhumeur, P. / Yuille, A. / IEEE Computer Society et al. | British Library Conference Proceedings | 1995




    Vehicle Information Storage Container with Video Recovering

    Yuvaraj, S. / Yokesh, G / Lalith Kishore, S et al. | IEEE | 2023