融合配准的多站室外大场景激光点云分割

针对室外场景范围广、分割难度大、识别效果不显著等问题,提出了一种融合多站点云配准的室外大场景分割方法.首先,根据室外场景视野大、点云数据量庞大特点,选取多个视角下重叠区域较多的建筑场景点集,结合SAC-IA和ICP方法进行点云自动配准,从而构建出点云密度相对均匀的室外大场景完整结构;然后,选用公共数据集Semantic...

Large Scene Segmentation of Outdoor Laser Point Cloud Based on Fusion and Registration

Aiming at the problem caused by the sparseness of outdoor laser point cloud scenes for semantic segmentation, a point cloud segmentation method based on deep learning is proposed. First, the laser point cloud scenes collected from five perspectives are processed, and parts of buildings with higher overlapping areas are selected in turn, and each group is registered by SAC-IA and ICP-based point cloud automatic registration methods. In order to construct a large outdoor scene with relatively uniform point cloud density, the public data set Semantic3D is used to train an outdoor point cloud segmentation model based on PointNet++, and the algorithm effect is verified on the test set. Finally, this model is used to segment the outdoor scene that has been constructed scenes and experimental results prove that point cloud scenes with multi-view registration can solve the problem of non-uniform sampling of point cloud scenes, so that the deep segmentation-based semantic segmentation model has a better recognition effect.