Registration and seamless fusion of point cloud from LiDAR and oblique photography

doi:10.13474/j.cnki.11-2246.2022.0101

Abstract

Abstract: The traditional and widely used urban space modeling methods such as laser point cloud and oblique photography have their own advantages and disadvantages. How to effectively integrate data from different sources and use them in the construction of city 3D models is the current difficulty in city modeling. Therefore, this paper proposes a precise registration and seamless fusion method for laser and oblique point clouds. This method can overcome the inconsistency of scale and accuracy of point cloud data from different sources, accurately calculate the spatial transformation relationship of data from different sources, and on this basis, data redundancy is eliminated, and the seamless integration of multi-source point cloud data is completed. Finally, this paper uses the data obtained in three sets of actual scenes to verify the effectiveness and accuracy of the elimination method in this paper. The experimental results show that the fusion data obtained by this method has better completeness and data accuracy than the single platform data.

Key words: point cloud registration, changing detection, 3D point cloud, 3D transformation, fusion

CLC Number:

RUAN Minghao, LU Yonghua, LIU Yuxian, TANG Shengjun, WANG Weixi, ZHANG Yuqi, LI You. Registration and seamless fusion of point cloud from LiDAR and oblique photography[J]. Bulletin of Surveying and Mapping, 2022, 0(4): 6-10.

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