We have developed a new algorithm that addresses the two major issues that are critical for the use of point-based rendering in real-world applications: rendering performance and rendering quality. The proposed algorithm improves rendering performance by reducing the number of points to be rendered. We generated points with different sizes in order to improve the quality of the point-splatting-type rendering. In this paper, we propose a feature-preserved simplification algorithm for point-sampled surfaces that generates models with different levels of details. The proposed method automatically balances the sampling density and point sizes. Our algorithm iteratively reduces the number of points using a bilateral filtering algorithm. We validate our method on the basis of the rendering results of different models with different resolutions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.