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Spatio-Temporal Image-Based Texture Atlases for Dynamic 3-D Models

Zsolt Janko 1, 2, 3 Jean-Philippe Pons 2, 3
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
2 imagine [Marne-la-Vallée]
CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech, LIGM - Laboratoire d'Informatique Gaspard-Monge
Abstract : In this paper, we propose a method for creating a high-quality spatio-temporal texture atlas from a dynamic 3-D model and a set of calibrated video sequences. By adopting an actual spatio-temporal perspective, beyond independent frame-by-frame computations, we fully exploit the very high redundancy in the input video sequences. First, we drastically cut down on the amount of texture data, and thereby we greatly enhance the portability and the rendering efficiency of the model. Second, we gather the numerous different viewpoint/time appearances of the scene, so as to recover from low resolution, grazing views, highlights, shadows and occlusions which affect some regions of the spatio-temporal model. Altogether, our method allows the synthesis of novel views from a small quantity of texture data, with an optimal visual quality throughout the sequence, with minimally visible color discontinuities, and without flickering artifacts. These properties are demonstrated on real datasets.
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Submitted on : Tuesday, November 24, 2009 - 12:41:04 PM
Last modification on : Tuesday, October 19, 2021 - 11:13:07 PM
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Zsolt Janko, Jean-Philippe Pons. Spatio-Temporal Image-Based Texture Atlases for Dynamic 3-D Models. IEEE International Workshop on 3-D Digital Imaging and Modeling, Oct 2009, Kyoto, Japan. pp.1646-1653, ⟨10.1109/ICCVW.2009.5457481⟩. ⟨inria-00435534⟩



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