The Three-dimensional Imaging Based on Mean Shift Algorithm

摘要：

The paper presents the surface clustering algorithm to remove the noise points of point cloud data for the three-dimensional imaging. The mean shift algorithm makes each sampling point to shift to the local maximum value of the kernel density function, and removes the noise points of point cloud data. Experiments show that the algorithm makes full use of the correlation and the local information of sampling points, not only removes most of the noise points but also retains the details, and gets a better threedimensional effect.

关键词： mean shift likelihood function three-dimensional imaging

作者: Limei Wang Bin Liu Jianwen Wang Qian Xu

作者单位: Shaanxi University of Science & Technology College of Electric & Information Engineering Xian, China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 506-509

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）