三维扫描点云优化网格重建与软件系统实现

Optimization and Mesh Reconstruction of 3D Scanning Points Cloud and Its Software System Implementation

物体经过三维扫描后获得大量的散乱点数据,为了能快速、准确的重建出网格曲面,提出了一种空间三角网格螺旋增长重建的算法。该算法首先利用包围球法对散乱点云进行优化,然后根据极坐标法确定螺旋增长的初始三角形,通过对生长的三角形最长边、最小内角和具有公共边的三角形所在面的二面角进行限制和对相应的新的网格边界点进行加锁和解锁操作,不断的寻找最佳扩展点,直到无可用的扩展点为止,最后再对有缝隙的网格边界进行缝合,完成三维扫描点云优化网格重建。

A large amount of scattered points data get from objects after 3D scanning, and in order to reconstruct mesh surface quickly and accuracy, a method of spatial spiral growth triangle mesh about mesh reconstruction is proposed. First, the algorithm puts forward a method of bounding ball to optimize the scattered points cloud. Then, a method based on polar coordinates determines the initial spiral growth triangle. A new triangle is based on the longest edge and minimum angle to be restricted. The dihedral angle of two triangles, which have a public side, is constantly looking for the best extension points; meanwhile, the corresponding points of new mesh boundary should to be locked and unlocked, until it has no extension points that are available. Then, stitches the crack which is on mesh boundary. Finally 3D scanning points cloud to optimize and mesh reconstruct have been completed.