利用影像序列修补三维激光点云孔洞方法研究
首发时间:2019-12-06
摘要:不同平台激光扫描设备由于扫描方式与视场角限制,一般都难以获取待测物体完整的点云数据,而根据摄影测量技术生成密集的影像点云,能获取复杂区域的测量数据。如何就两种平台获取的点云数据优势信息和互补需求进行孔洞修补是近年来智慧城市建设的重点研究内容。本文针对三维激光点云数据外业采集缺失的原因,结合影像点云特点,提出了一种改进的尺度迭代最近点(SICP)算法完成缺失部分点云修补工作,并通过对比分析证明了本文方法的可行性。
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Research on Mending Three Dimensional Point Clond Hole Method with Photogrammetry
Abstract:Due to the scanning mode and the viewing angle limitation of different platform laser scanning devices, it is generally difficult to obtain complete point cloud data of the object to be tested. According to the photogrammetric technology, a dense image point cloud is generated, and measurement data of a complex area can be obtained. How to combine the advantage information and complementary requirements of point cloud data acquired by the two platforms for hole repair is the key research content of smart city construction in recent years. In view of the reasons for the lack of 3D laser point cloud data field acquisition, combined with the characteristics of image point cloud, an improved scale iterative closest point (SICP) algorithm is proposed to complete the missing part cloud repair work, and the method is proved by comparative analysis.
Keywords: 3D laser point cloud image point cloud hole mend SICP algorithm
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