一种三维重建技术中基于点云粗配准方法

Point cloud coarse registration method in 3D reconstruction technology

伴随着计算机技术应用与三维扫描应用的发展,点云三维重建技术被普遍的应用到计算机辅助设计、虚拟现实、测量学、医学等各种领域.选取了斯坦福大学提供的点云数据作为研究对象,提出了从点云配准,点云降采样,点云滤波到重建三角面的实现方案.通过粗配准算法处理点云,使用精配准ICP算法;经过配准得到的点云降采样;采用双边滤波平滑点云;重建点云模型.通过对比斯坦福大学提供的重建后的模型,结果表明,本文的方法在点云三维重建方面有较好的表现.

With the development of computer technology applications and 3D scanning applications,point cloud 3D reconstruction technology has been widely applied to computer-aided design,virtual reality,surveying,medicine and other fields.The point cloud data provided by Stanford University was selected as the research object,and the implementation scheme from point cloud registration,point cloud down sampling,point cloud filtering to reconstruction triangle surface was proposed.The point cloud was processed by the coarse registration algorithm,and the fine-aligned ICP algorithm was used;the point cloud down-sampling was obtained by registration;the point cloud was smoothed by bilateral filtering;the point cloud model was reconstructed by triangulation.By comparing the reconstructed models provided by Stanford University,the results showed that the proposed method had a good performance in point cloud 3D reconstruction.