Abstract Given a collection of images of offices, what would we say we see in the images? The objects of interest are likely to be monitors, keyboards, phones, etc. Such identification of the foreground in a scene is important to avoid distractions caused by background clutter and facilitates better understanding of the scene. It is crucial for such an identification to be unsupervised to avoid extensive human labeling as well as biases induced by human intervention. Most interesting scenes contain multiple objects of interest. Hence, it would be useful to separate the foreground into the multiple objects it contains. We propose dISCOVER, an unsupervised approach to identifying the multiple objects of interest in a scene from a collection of images. In order to achieve this, it exploits the consistency in foreground objects - in terms of occurrence and geometry - across the multiple images of the scene.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unsupervised Identification of Multiple Objects of Interest from Multiple Images: dISCOVER


    Beteiligte:
    Parikh, Devi (Autor:in) / Chen, Tsuhan (Autor:in)


    Erscheinungsdatum :

    01.01.2007


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Identification and velocity computation of multiple moving objects in images

    Mahmoud, S.A. / Afifi, M.S. / Green, R.J. | IEEE | 1990



    Surface Description of Complex Objects from Multiple Range Images

    Chen, Y. / Medioni, G. / Institute of Electrical and Electronics Engineers; Computer Society | British Library Conference Proceedings | 1994


    Unsupervised texture classification: Automatically discover and classify texture patterns

    Qin, L. / Zheng, Q. / Jiang, S. et al. | British Library Online Contents | 2008


    Consensus Surfaces for Modeling 3D Objects from Multiple Range Images

    Wheeler, M. D. / Sato, Y. / Ikeuchi, K. et al. | British Library Conference Proceedings | 1998