A New Adaptive Mesh Simplification Method Using Vertex Clustering with Topology-and-Detail Preserving

A new adaptive mesh simplification method based on vertex clustering is presented in this paper, which can preserve the model topology and subtle geometric features better than traditional vertex-clustering methods. Guided by the normal vectors corresponding to all vertices, the proposed method adopts a binary tree structure to split the bounding box of the inputting model adaptively. This subdivision does not stop unless all triangles in the cells are considered to be flat enough or the cell is small enough. Then the representative vertex for each cell is calculated according to the quadric error metric. Experimental results have demonstrated that the presented method is fast and can guarantee displayable results with good quality. In addition, it also addresses the problem of view-dependent simplification.