摘要
点云配准是集成车载和航空LiDAR数据进行三维建筑模型构建的重要环节。以建筑轮廓为配准基元,提出一套完整的车载和航空LiDAR数据配准流程,包括点云数据中建筑轮廓的提取、基于建筑轮廓的点云配准两个步骤。首先提出一种极大值累积量的方法,以实现车载LiDAR点云中建筑轮廓的提取;在利用建筑轮廓进行初始配准的基础上,采用配准关系修正的方法以精确配准点云。试验证明,极大值累积量方法能够有效地从车载LiDAR点云中提取建筑轮廓,此配准方法能够实现车载和航空LiDAR数据的高精度配准。
Point cloud registration is a key point for building model reconstruction with vehicle and airborne LiDAR. Taking building contours as registration primitives, a complete workflow is proposed for the registration of vehicle and airborne LiDAR. The proposed approach includes two main steps, building contour extraction from vehicle and airborne LiDAR and a registration method with building contours. First a high value accumulation method is proposed for the extraction of vehicle building contours from vehicle LiDAR; then, based on the initial registration result of building contours, a modification method for registration matrix is used for the fine registration of point cloud. The experiment shows that, the proposed high value accumulation method is effective for the extraction of building contours from vehicle LiDAR and the registration approach is able to register vehicle and airborne LiDAR data with high precision.
出处
《测绘学报》
EI
CSCD
北大核心
2013年第5期699-706,714,共9页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(41001238)
国家科技支撑计划(2012BAH28B02)
