关键词: 点云重建, 误差驱动, 紧支撑径向基函数, 曲面插值

Abstract: This paper puts forward a reconstruction algorithm based on the error driver，the successive iterative approximation and large-scale 3D scattered data.This paper re-samples the point cloud data，using normalized CSRBF as interpolation function（RBF），then interpolates to a small amount of points data which has been re-sampled.After that the points that don’t attend interpolation will be put into the implicit function equation to calculate error.The points whose error beyond certain threshold will be re-sampled，then they are put into the original sample point set and restart the interpolation.After multiple iterative operation，the minimum points can be used to do interpolation on the original point cloud model.Experimental results show that this algorithm has higher robustness and higher efficiency.

Key words: point cloud reconstruction, error driver, Compactly Supported Radial Basis Function（CSRBF）, surface interpolation