Industrial Design Applications of Surface Reconstruction Algorithm Based on Three Dimensional Point Cloud Data

Abstract

At present, rapid reconstruction of amounts of point cloud data is still scarce, so is for the time complexity and space complexity in current methods. This article puts forward an adaptive rasterizing-based triangular mesh reconstruction towards amounts of data simplification reconstruction for storage and transmission. Our measure improves the region expansion: first, macro-estimation method with various points non-difference will obtain 3D grid of side length and separate point cloud data into grid unit. Then, by selecting data points in basic units as seed point and setting triangle side length to approximate positive neighborhood as restriction in order to construct initial triangle grid. Finally, triangle grid reconstruction is completed by layer-by-layer expansion. From experimental results it can be seen, point cloud simplification in high density is faster in reconstruction speed and it has effective robustness.