An iterative slicing reconstruction method for point cloud surface holes

Abstract

An iterative slicing reconstruction method for point cloud surface holes is proposed to address the problem that the traditional hole repair method fails in repairing surface holes with uneven density. Firstly, the least squares micro-slices are used to detect and extract the point cloud hole boundaries, and then the least enclosing box is constructed and initially rasterized to achieve a uniform segmentation effect. Then the density of segmentation results is analyzed and judged, and if the density is too large, iterative slicing calculation is performed to obtain uniformly dense segmentation blocks. Finally, the moving least squares method is used to fit each slice data to reconstruct the missing part of the point cloud surface.Our results show that this method can achieve the effect of filling the point cloud holes and averaging the point cloud density as well as improving the accuracy of hole repair for holes containing curved surfaces or point cloud data with uneven density.