摘要
为提高点云查询效率和按需提取数据,提出一种二维与三维混合索引的大规模点云数据管理方法。采用二维四叉树和三维最小外包盒结构管理原始点云,以3D-R树管理多站点云,利用对象关系数据库管理全部点云模型和相关属性数据。利用古建筑大规模点云数据在微机上实现了点云模型的数据存储与可视化。结果表明本方法能够管理超过10 GB级的点云模型数据和十亿级有效点,数据可视化效率较高。
A database management algorithm based on combined 2D and 3D indexing of very large point-cloud data is proposed,for extracting the point cloud in need and improving the query efficiency.Single-station point-cloud is managed with 2D quad tree and 3D MBB structure.Multi-station point-clouds are indexed with 3D-R tree.Finally the organized hierarchical model and other attribute data are stored in ralation-object database.The data storage,management and visualization of very large point-clouds are implimented on personal computer with massive point clouds from the ancient buildings such as Forbidden City.Result shows that the algorithm is able to manage more than 10 GB-level data and one billion effective points with satisfactory drawing efficiency.
出处
《测绘学报》
EI
CSCD
北大核心
2012年第4期605-612,共8页
Acta Geodaetica et Cartographica Sinica
基金
北京市自然科学基金重点项目(B类)(KZ200910016001)
北京市属高等学校人才强教深化计划“高层次人才资助计划”(PHR20110511)
