Commodity 3D display based on point cloud reconstruction

Commodity display is very important in online shopping. In this paper, a method of reconstructing the commodity 3D model is proposed. Firstly, this paper accepts point clouds of a commodity from different angles. Secondly, before initial alignment, this paper compresses point clouds based on octree. Thirdly, this paper aligns all point clouds. At last, we reconstruct the commodity surface. In this step, a point cloud smoothing algorithm based on MLS and a Delaunay growth projection algorithm are proposed. Experimental results demonstrate that the computation time consumed by our improved registration algorithm is only one sixth of that of traditional one. And the quality only decreases slightly. The commodity 3D model has been successfully and efficiently reconstructed.