A FEATURE PRESERVING ALGORITHM FOR POINT CLOUD SIMPLIFICATION BASED ON HIERARCHICAL CLUSTERING
发布时间：2025-01-07 点击次数：
DOI码：10.1109/igarss.2016.7730457
所属单位：School of Remote Sensing and Information Engineering, Wuhan University, China
发表刊物：2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
关键字：point cloud,simplification,surface variation,hierarchical clustering,feature points
摘要：The efficiency and accuracy loss are the key issues for the point cloud simplification. In this paper, a feature preserving algorithm is proposed for point cloud simplification based on hierarchical clustering with the surface feature description. The surface variation is presented as the main criterion for the efficient hierarchical clustering method to simplify the mass and dense point cloud fast, meanwhile we retain the feature points to ensure a small accuracy loss. The experiment results show that the proposed method is efficient and has a good effect to maintain the features as the same degree of simplification.
合写作者： Qingwu,Hu,Zhao, Yue,Wang, Pengcheng
论文类型：会议论文
学科门类：工学
文献类型：C
页面范围：5581-5584
ISSN号：2153-6996
是否译文：否
CN号：WOS:000388114605131
发表时间：2016-07-10
