Multi-view Reconstruction and Texturing

Ehsan Aganj 1, 2, 3
1 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
Abstract : In this thesis, we study the problem of static and dynamic multiview reconstruction and texturing, particularly focusing on real applications. First, we propose three reconstruction methods sharing the objective of estimating a representation of a static/dynamic scene from a set of multiple images/videos. Then, we consider the problem of multi-view texturing, focusing on the visual correctness of the rendering. The contributions of this thesis are as follows : 1. A shape from silhouette approach is proposed producing a compact and high- quality 4D representation of the visual hull, o ering easy and extensive control over the size and quality of the output mesh as well as over its associated reprejection error. 2. A dynamic multi-view reconstruction method is proposed computing a 4D representation of a dynamic scene, based on a global optimization of a true spatio-temporal energy, taking visibility into account. 3. A photo-consistent surface reconstruction method is proposed incorporating the input images for better accuracy and robustness. 4. A multi-view texturing method is proposed computing a visually correct tex- turing of an imprecise mesh.
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Ehsan Aganj. Multi-view Reconstruction and Texturing. Computer Vision and Pattern Recognition [cs.CV]. Ecole des Ponts ParisTech, 2009. English. ⟨NNT : 2009ENPC0918⟩. ⟨pastel-00517742⟩

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