吉林大学学报（理学版）2018，Vol.56Issue(3)：692-696,5.DOI:10.13413/j.cnki.jdxblxb.2018.03.37
最小二乘支持向量机的点云数据孔洞修补算法
Hole Repairing Algorithm for Point Cloud Data Based on Least Square Support Vector Machine
摘要
Abstract
In order to obtain the ideal hole repairing result of point cloud data ,aiming at the defects existing in the current algorithms ,we proposed a hole repairing algorithm for point cloud data based on least square support vector machine .First ,the hole repairing range was estimated according to the boundary of scattered point cloud ,and then according to information of hole and surrounding points , we built a surface by least square support vector machine ,and repaired the hole in the point cloud data . Finally , the simulation experiment was realized by C+ + language programming . The experimental results show that the least square support vector machine can effectively repair various complex holes ,and the repair effect is better than other algorithms .关键词
三维成像/曲面重建/点云数据/孔洞修补/最小二乘支持向量机Key words
three-dimensional imaging/surface reconstruction/point cloud data/hole repairing/least square support vector machine (LSSVM )分类
信息技术与安全科学引用本文复制引用
杨永强,李淑红..最小二乘支持向量机的点云数据孔洞修补算法[J].吉林大学学报（理学版）,2018,56(3):692-696,5.基金项目
国家自然科学基金(批准号:61202285). （批准号:61202285）
