Simplification of Point Set Surfaces using Bilateral Filter and Multi-Sized Splats

Abstract

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.

Variational Shape Approximation of Point Set Surfaces

“…This requires a specific focus on features represented by the point sets. By utilizing a bilateral filtering, both Euclidean distances and normal information can be taken into account throughout a simplification process on a point set to best preserve both the large-scale geometry and small-scale features, in Sosorbaram et al (2010). While these methods are feature-preserving, they are not robust in the presence of outliers or noise.…”