摘要
针对车载全景影像与激光点云数据融合的研究不足的现状,文章给出了一种适合球面全景影像的车载彩色点云生成方案:由车载POS数据及系统标定参数可获得全景影像的外方位元素,依据影像的采集视角选择激光点最佳的关联影像,然后以球面投影为成像模型获得激光点在影像上的颜色属性值,进而获得彩色点云数据;并对融合的误差进行了讨论与分析。经过融合后的彩色点云几何精度高、目视效果好,使两种数据源的优势得到了有效的结合。实验结果验证了这种方法的可行性和准确性。
Aiming at the current status that the study on the fusion of vehicle-borne panoramic images and LiDAR point clouds is insufficient, the paper proposed a method of vehicle-borne colored point cloud generation： the exterior orientation elements of panoramic images were calculated with vehicle-borne POS data and systematic calibration parameters, images associated with optimal laser point clouds were selected based on the viewing angles of image capture, and the color value in the image corresponding to the laser point was achieved by using the spherical projection as the imaging model, then the colored point clouds were obtained. Finally, the error on the fusion was analyzed. Result showed that the fused colored point cloud would have high geometric accuracy and good visual performance, demonstrating the advantages of both data sources, which proved the feasibility of the method.
出处
《测绘科学》
CSCD
北大核心
2015年第9期111-114,162,共5页
Science of Surveying and Mapping
基金
精密工程与工业测量国家测绘地理信息局重点实验室开放基金项目(PF2013-11)
关键词
车载
全景
激光点云
融合
彩色点云
vehicle-borne
panoramic
laser point cloud
tusion
colored point cloud
