Rapid Visualization of Large Point-Based Surfaces
BOUBEKEUR, Tamy
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
SCHLICK, Christophe
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
BOUBEKEUR, Tamy
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
SCHLICK, Christophe
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
< Réduire
Visualization and manipulation of complex data on wireless mobile devices [IPARLA]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Langue
en
Communication dans un congrès
Ce document a été publié dans
EUROGRAPHICS International Symposium on Virtual Reality, Archeology and Cultural Heritage (VAST), 2005-11-08, Pise. 2005
Eurographics
Résumé en anglais
Point-Based Surfaces can be directly generated by 3D scanners and avoid the generation and storage of an explicit topology for a sampled geometry, which saves time and storage space for very dense and large objects, such ...Lire la suite >
Point-Based Surfaces can be directly generated by 3D scanners and avoid the generation and storage of an explicit topology for a sampled geometry, which saves time and storage space for very dense and large objects, such as scanned statues and other archaeological artefacts [Duguet 2004]. We propose a fast processing pipeline of large point-based surfaces for real-time, appearance preserving, polygonal rendering. Our goal is to reduce the time needed between a point set made of hundred of millions samples and a high resolution visualization taking benefit of modern graphics hardware, tuned for normal mapping of polygons. Our approach starts by an out-of-core generation of a coarse local triangulation of the original model. The resulting coarse mesh is enriched by applying a set of maps which capture the high frequency features of the original data set. We choose as an example the normal component of samples for these maps, since normal maps provide efficiently an accurate local illumination. But our approach is also suitable for other point attributes such as color or position (displacement map). These maps come also from an out-of-core process, using the complete input data in a streaming process. Sampling issues of the maps are addressed using an efficient diffusion algorithm in 2D. Our main contribution is to directly handle such large unorganized point clouds through this two pass algorithm, without the time-consuming meshing or parameterization step, required by current state-of-the-art high resolution visualization methods. One of the main advantages is to express most of the fine features present in the original large point clouds as textures in the huge texture memory usually provided by graphics devices, using only a lazy local parameterization. Our technique comes as a complementary tool to high-quality, but costly, out-of-core visualization systems. Direct applications are: interactive preview at high screen resolution of very detailed scanned objects such as scanned statues, inclusion of large point clouds in usual polygonal 3D engines and 3D databases browsing.< Réduire
Mots clés en anglais
Large models
out-of-core processing
normal mapping
appearance preserving
output sensitive conversion
point-based graphics
Origine
Importé de halUnités de recherche