Abstract
In this paper, we present a novel method for surface sampling and remeshing with good blue-noise properties. Our approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality blue-noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue-noise properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior to the current state-of-the art approaches.
Original language | English (US) |
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Pages (from-to) | 167-176 |
Number of pages | 10 |
Journal | Computer Graphics Forum |
Volume | 33 |
Issue number | 5 |
DOIs | |
State | Published - Aug 2014 |
Keywords
- Categories and Subject Descriptors (according to ACM CCS)
- I.3.6 [Computer Graphics]: Methodology and Techniques - Blue-noise sampling and remeshing
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design