Most of the algorithms dealing with image based 3-D reconstruction involve the evolution of a surface based on a minimization criterion. The mesh parametrization, while allowing for an accurate surface representation, suffers from the inherent problems of not being able to reliably deal with self-intersections and topology changes. As a consequence, an important number of methods choose implicit representations of surfaces, e.g. level set methods, that naturally handle topology changes and intersections. Nevertheless, these methods rely on space discretizations, which introduce an unwanted precision-complexity trade-off. In this paper we explore a new mesh-based solution that robustly handles topology changes and removes self intersections, therefore overcoming the traditional limitations of this type of approaches. To demonstrate its efficiency, we present results on 3-D surface reconstruction from multiple images and compare them with state-of-the art results.


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    Titel :

    TransforMesh : A Topology-Adaptive Mesh-Based Approach to Surface Evolution


    Beteiligte:
    Yagi, Yasushi (Herausgeber:in) / Kang, Sing Bing (Herausgeber:in) / Kweon, In So (Herausgeber:in) / Zha, Hongbin (Herausgeber:in) / Zaharescu, Andrei (Autor:in) / Boyer, Edmond (Autor:in) / Horaud, Radu (Autor:in)

    Kongress:

    Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007


    Erschienen in:

    Computer Vision – ACCV 2007 ; Kapitel : 17 ; 166-175


    Erscheinungsdatum :

    2007-01-01


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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