基于半边折叠的优化算法

An optimization algorithm based on half edge collapse

针对引入距离和曲率的半边折叠算法在保持特征点和边界点方面的不足,介绍了一种基于半边折叠的优化算法。该算法在折叠过程中识别特征点与边界点,并通过引入边界点系数、顶点度、折叠点到相邻点距离均值的平方根以及比例系数,计算折叠代价,排序折叠优先级,优先折叠非特征点和非边界点,文中的边界点是指模型裂缝处的点。实验结果验证了该算法对于特征点集多且分散的模型以及不完全封闭模型保存特征点、边界点的可行性。

Aiming at insufficiently keeping feature points and boundary points of distance and curvature for the half-edge collapse method, it presents an improved algorithm based on half-edge collapse. This method checks the feature points and the boundary points in the process of folding and utilizes boundary point coefficient, vertex degree, positive square root of the average distance from the folding point to all of its adjacent points and scale coefficient to calculate the collapse cost, sorts the folding priority and gives the priority to fold the non-feature points and the points not on the boundary. The boundary points refer to points of the fracture in the model. Ex- periments prove that this method can effectively preserve the feature and boundary point set for model with scat- tered feature point sets and incomplete closure model.