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.
- 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