Paper Info
Title
A Subdivision Framework for Partition of Unity Parametrics.
Abstract
Partition of Unity Parametrics (PUPs) are a generalization of NURBS that allow us to use arbitrary basis functions for modeling parametric curves and surfaces. One interesting problem is finding subdivision schemes for this recently developed and flexible class of parametrics. In this paper, we introduce a systematic approach for determining uniform subdivision of PUPs curves and tensorproduct surfaces. Our approach formulates PUPs subdivision as a least squares problem, which enables us to find exact subdivision filters for refinable basis functions and optimal approximate schemes for irrefinable ones. To illustrate this approach, we provide sample subdivision schemes with different properties, which are further demonstrated by presenting various examples.
Year
DOI
Venue
2016
10.20380/GI2016.04
Graphics Interface
Field
DocType
Citations 
Least squares,Computer vision,Discrete mathematics,Parametric equation,Partition of unity,Algebra,Computer science,Subdivision,Basis function,Artificial intelligence
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Amirhessam Moltaji100.34
Adam Runions222214.87
Faramarz Samavati320923.91