Multiresolution wavelet analysis for simplification and visualization of multitextured meshes

Marc F. Toubin; David L. Page; Christophe Dumont; Frederic Truchetet; Mongi A. Abidi

doi:10.1117/12.378891

28 February 2000 Multiresolution wavelet analysis for simplification and visualization of multitextured meshes

Marc F. Toubin, David L. Page, Christophe Dumont, Frederic Truchetet, Mongi A. Abidi

Proceedings Volume 3960, Visual Data Exploration and Analysis VII; (2000) https://doi.org/10.1117/12.378891
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

This paper describes a method to reduce multi-texture 3D meshes using a multi-resolution wavelet analysis. Large and dense multi-modal meshes require new methods for efficient display. In this paper, we present a mesh simplification process, that inherently deals with multi-dimensional data set, controlled in a feature space composed of geometry, curvature, and the textures themselves. The result of the wavelet analysis using a multi-resolution analysis (MRA) based on the 2D quincunx-wavelet transform is considered as texture map called the 'detail relevance'. Virtual range and texture images are captured from selected viewpoints located around the object. The detail extraction is achieved using a multi-resolution approach based on the wavelet cascade analysis. The MRA process extracts detail information at various resolutions and produces a texture image that shows the relevance information attached to each vertex of the mesh. The user has input in this process to select what resolutions are more relevant than others. This approach is useful for filtering noise, preserving discontinuities, mining for surface details, reducing data, and many other applications. We present simplification results of digital elevation maps and 3D objects.

Citation Download Citation

Marc F. Toubin, David L. Page, Christophe Dumont, Frederic Truchetet, and Mongi A. Abidi "Multiresolution wavelet analysis for simplification and visualization of multitextured meshes", Proc. SPIE 3960, Visual Data Exploration and Analysis VII, (28 February 2000); https://doi.org/10.1117/12.378891

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available