【摘要】 三角网格分割是三维模型处理中一项重要的工作,通过VSA(variational shape approximation)方法分割的结果可以用于轮廓线的生成、模型重建等工作,但由于其种子点选取的随机性,直接通过VSA方法进行不同类型的网格划分会存在划分粒度、划分策略不确定的问题。文章针对三维模型轮廓线提取,基于VSA方法,提出一种三角网格分割中种子点的优化采样算法,通过优化种子点的位置和数量,提升分割效果,生成质量较高的轮廓线。通过对多个模型进行试验表明,利用文中提供的种子点优化采样方法,可以保证在种子点数量尽可能少的情况下,重建质量较高的模型。更多还原

【Abstract】 Triangular mesh segmentation is an important work in 3 D model processing. The results obtained by variational shape approximation(VSA) method can be used for contour generation and remeshing. However, due to the randomness of the selection of seed points, different types of mesh division directly through VSA method will have some uncertain problems in terms of segmentation granularity and segmentation strategy. In this paper, aiming at contour extraction of 3 D models, mesh method is proposed to optimize the location and quantity of seed points in segmentation. By optimizing the location and quantity of seed points, the segmentation result is improved and contour lines with high quality are generated. Experiments on several models show that the optimal sampling method of seed points provided by the proposed method can be used to reconstruct the high-quality model with as few seed points as possible.更多还原