Fairing of Polygon Meshes Via Bayesian Discriminant Analysis

Abstract

Design of an anisotropic diffusion-based filter that performs Bayesian classification for automatic selection of a\nproper weight for fairing polygon meshes is proposed. The data analysis based on Bayesian classification is\nadopted to determine the decision boundary for separating potential edge and non-edge vertices in the curvature\nspace. The adaptive diffusion filter is governed by a double-degenerate anisotropic equation that determines how\neach polygon vertex is moved along its normal direction in the curvature space iteratively until a steady state is\nreached. The determination of how much a polygon vertex should be moved depends on whether it is a potential\nedge or a non-edge vertex. At each fairing step, conceptually, a bi-directional curvature map whose boundary\nline while couched by the weight value can be plotted to understand the type of a vertex. Experimental results\nshow that the proposed diffusion-based approach could effectively smooth out noises while retaining useful data\nto a very good degree.