基于逆Loop细分的半正则网格简化算法

A semi-regular mesh simplification algorithm based on inverse Loop subdivision

三维网格简化是在保留目标物体几何形状信息的前提下尽量减小精细化三维模型中的点数和面数的一种操作,对提高三维网格数据的存取和网络传输速度、编辑和渲染效率具有十分重要的作用。针对大多网格简化算法在简化过程中未考虑网格拓扑结构与视觉质量的问题,提出了一种基于逆Loop细分的半正则网格简化算法。首先根据邻域质心偏移量进行特征点检测,随后随机选取种子三角形,以边扩展方式获取正则区域并执行逆Loop细分进行简化。最后,以向内分割方式进行边缘拼接,获取最终的简化模型。与经典算法在公开数据集上进行实验对比,结果表明,该算法能够在简化的同时有效地保持网格特征,尽可能保留与原始网格一致的规则的拓扑结构,并且在视觉质量上优于边折叠以及聚类简化算法。

3D mesh simplification is an operation to minimize the number of vertices and faces in the refined 3D model while preserving the geometric information of the target object.It plays a significant role in improving the access and network transmission speed of the 3D mesh data,and the efficiency of editing and rendering.To address the problem of most mesh simplification algorithms neglecting the mesh topology and visual quality during simplification,a semi-regular mesh simplification algorithm was proposed based on the inverse Loop subdivision.The algorithm first detected the feature points according to the neighborhood centroid offset.Then a seed triangle was randomly selected to obtain the regular region by edge extension,and the inverse Loop subdivision was performed to simplify the mesh.Finally,the simplified model was gained by edge splicing in the way of inwards segmentation.Regarding the open testing data,comparisons were made between the algorithm and the classical ones.The experimental results show that the proposed algorithm can preserve the features effectively and keep the regular topology structure as much as possible during simplification,and that it is superior to the edge collapse and clustering algorithm in visual quality.