Yan, Dong-MingGuo, JianweiJia, XiaohongZhang, XiaopengWonka, PeterThomas Funkhouser and Shi-Min Hu2015-03-032015-03-0320141467-8659https://doi.org/10.1111/cgf.12442In 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.