Edge Collapse Simplification Based on Weighted Quadric Error Metrics

After drastic simplification process, most of the existing simplification algorithms based on edge collapse do not preserve important shape features of the original model very well and lead to visual distortion. This paper presents two edge-collapse based algorithms using improved quadric error metrics. Two important degrees of a triangle are given and embedded into the original Garland' s quadric error metrics, so that the metrics can not only measure distance error but also reflect geometric variations of local surface. The experimental results show that the novel algorithms can preserve quite a number of important shape features and reduce visual distortion even after performing drastic level of simplification.