Paper Info
Title
Layered Depth-Normal Images: a Sparse Implicit Representation of Solid Models
Abstract
This paper presents a novel implicit representation of solid models. With this representation, every solid model can be effectively presented by three layered depth-normal images (LDNIs) that are perpendicular to three orthogonal axes respectively. The layered depth-normal images for a solid model, whose boundary is presented by a polygonal mesh, can be generated efficiently with help of the graphics hardware accelerated sampling. Based on this implicit representation - LDNIs, solid modeling operations including the Boolean operations and the offsetting operation have been developed. A contouring algorithm is also introduced in this paper to generate thin structure and sharp feature preserved mesh surfaces from the layered depth-normal images. Comparisons between LDNIs and other implicit representation of solid models are given at the end of the paper to demonstrate the advantages of LDNIs.
Year
Venue
Keywords
2010
Clinical Orthopaedics and Related Research
computational geometry,graphics hardware,solid modeling
Field
DocType
Volume
Discrete mathematics,Perpendicular,Polygon,Graphics hardware,Computer science,Algorithm,Constructive solid geometry,Theoretical computer science,Solid modeling,Sampling (statistics),Orthogonal coordinates,Contouring
Journal
abs/1009.0
Citations 
PageRank 
References 
4
0.46
18
Authors
2
Name
Order
Citations
PageRank
Charlie C. L. Wang11280100.10
Yong Chen25212.67