Uniform Sampling in Geodesic Metric for LOD Generation

Abstract

This paper describes a level-of-detail generation approach for large scale models. To make LODs preserve the overall appearance of original data, the presented approach is to perform uniform sampling in geodesic metric, resulting in adaptive meshes or points in Euclidean metric. Geometric attribute such as curvature help to establish geodesic metric and therefore control the sampling ratios in different regions. This method is rather simple and LODs are very fit for display. Some cases are provided to illustrate the capability and feasibility of the method for both meshes and unorganized points.