Commodity 3D display based on point cloud reconstruction

Yujie Fu, Tong Jia, Zhaozhan Song, Bo Peng
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Abstract

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.
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基于点云重构的商品三维展示
商品展示在网上购物中非常重要。本文提出了一种重构商品三维模型的方法。首先,本文从不同角度对某一商品的点云进行了接受。其次,在初始对齐之前,基于八叉树对点云进行压缩。第三,对所有点云进行对齐。最后,对商品表面进行重构。在这一步中,提出了基于MLS的点云平滑算法和Delaunay增长投影算法。实验结果表明,改进配准算法的计算时间仅为传统配准算法的六分之一。而且质量只是略有下降。成功、高效地重建了商品三维模型。
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