Parallel adaptive simplification of massive meshes

A parallel simplification method based on vertex clustering for out-of-core meshes is presented in this paper. To reduce file I/O, only one linear scan is performed in this method to partition the original model into equal batches. Then vertex normal vectors and coefficients of each triangle plane are calculated with some inter-task communications. The portion assigned to each processor is simplified by an improved vertex clustering method. Finally, all reduced data are sent back to the master node and assembled into the simplified mesh. The partition stitching is fulfilled simply by using a global vertex index. A lot of experiments have demonstrated that the proposed method can handle extremely large data set and speed up the execution time obviously as well as produce approximations with high quality.