八叉树
点云
分割
计算机科学
代表(政治)
特征(语言学)
过程(计算)
人工智能
激光扫描
体素
点(几何)
计算机视觉
区域增长
模式识别(心理学)
图像分割
尺度空间分割
数学
激光器
几何学
操作系统
语言学
哲学
物理
光学
政治
政治学
法学
作者
Anh Vu Vo,Linh Truong-Hong,Debra F. Laefer,Michela Bertolotto
出处
期刊:Isprs Journal of Photogrammetry and Remote Sensing
日期:2015-06-01
卷期号:104: 88-100
被引量:436
标识
DOI:10.1016/j.isprsjprs.2015.01.011
摘要
This paper introduces a novel, region-growing algorithm for the fast surface patch segmentation of three-dimensional point clouds of urban environments. The proposed algorithm is composed of two stages based on a coarse-to-fine concept. First, a region-growing step is performed on an octree-based voxelized representation of the input point cloud to extract major (coarse) segments. The output is then passed through a refinement process. As part of this, there are two competing factors related to voxel size selection. To balance the constraints, an adaptive octree is created in two stages. Empirical studies on real terrestrial and airborne laser scanning data for complex buildings and an urban setting show the proposed approach to be at least an order of magnitude faster when compared to a conventional region growing method and able to incorporate semantic-based feature criteria, while achieving precision, recall, and fitness scores of at least 75% and as much as 95%.
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