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Proceedings Paper

Multiresolution analysis of 3D multimodal objects using a 2D quincunx wavelet analysis
Author(s): Marc F. Toubin; Christophe Dumont; Frederic Truchetet; Mongi A. Abidi
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Paper Abstract

A reconstructed scene in virtual reality typically consists of millions of triangles.Data are heterogeneous and consist not only of geometric coordinates but also of multi-modal data. The latter requires more complex calculations and very high-speed graphics. Due to the large amount of data, displaying and analyzing these 3D models require new methods. This paper present an innovative method to analyze multi-model models using a 2D-quincunx wavelet analysis. The algorithm is composed of three processes. First, a set of range images is captured from various viewpoints surrounding the object of interest. In addition, a set of multi-modal images is acquired. Then, a multi-resolution analysis based on the quincunx wavelet transform is performed. The multi- resolution analysis allows extraction of multi-resolution detail areas. These areas of details are projected back onto the surface of the initial model. Detail areas are marked onto the model and constitute another modality. Finally, a mesh simplification is performed to reduce data that are not marked as detail. This approach can be applied to any 3D models containing multi-modal information in order to allow fast rendering and manipulation. This method also allows 3D data de-noising.

Paper Details

Date Published: 26 August 1999
PDF: 9 pages
Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); doi: 10.1117/12.360307
Show Author Affiliations
Marc F. Toubin, Univ. de Bourgogne (France) and Univ. of Tennessee/Knoxville (France)
Christophe Dumont, Univ. de Bourgogne (France) and Univ. of Tennessee/Knoxville (United States)
Frederic Truchetet, Univ. de Bourgogne (France)
Mongi A. Abidi, Univ. of Tennessee/Knoxville (United States)


Published in SPIE Proceedings Vol. 3837:
Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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