DocumentCode
414124
Title
Efficient view-dependent LOD control for large 3D unclosed mesh models of environments
Author
Feng, Jie ; Zha, Hongbin
Author_Institution
Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
Volume
3
fYear
2004
fDate
26 April-1 May 2004
Firstpage
2723
Abstract
The rapid progress of 3D modeling techniques have brought more and more applications of 3D range data in robotics. However, the 3D data we acquire with range finders mounted on mobile robots are usually too large to process in real-time, and holes and boundaries are unavoidable on the surface it represents. One method to resolve this problem is to perform mesh simplification and level of detail (LOD) control on these models. A new method based on progressive meshes (PMs) is proposed in this paper, which adopts different simplification and remeshing strategies on different boundary conditions, and therefore well preserves geometrical features on the boundaries through the simplification. The detail records are organized in a forest-shaped data structure at the same time. Hence, when a scene is reconstructed using the multiresolution models, the local details can be rapidly added by selective refinement. Furthermore, continuous view-dependent distributions of LOD are also supported to provide efficient scene representation and rendering.
Keywords
data structures; distance measurement; mobile robots; 3D modeling techniques; continuous view-dependent distributions; forest-shaped data structure; large 3D unclosed mesh models; level-of-detail control; mesh simplification; mobile robots; progressive meshes; range finders; robotic 3D range data; scene representation; view-dependent LOD control; Boundary conditions; Coherence; Data structures; Image reconstruction; Laser modes; Layout; Mobile robots; Sonar navigation;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
ISSN
1050-4729
Print_ISBN
0-7803-8232-3
Type
conf
DOI
10.1109/ROBOT.2004.1307472
Filename
1307472
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