Laser 3D realistic reconstruction and lightweight access method based on LiDAR point cloud

In complex outdoor environments, processing a large amount of point cloud data and restoring the precise structure of real scenes is a key difficulty in real scene reconstruction. To this end, a laser 3D real scene reconstruction and lightweight access method based on LiDAR point cloud is proposed. Using region growing algorithm to segment laser foot points of buildings in 3D reality and obtain LiDAR point cloud data of 3D reality. Using the Euler Lagrange equation to establish a 3D data field for laser 3D real scene image reconstruction, and completing the 3D reconstruction of laser 3D real scene images. Using SSD lightweight algorithm to perform regression classification on the extracted target features, in order to locate targets of different scales and achieve lightweight access to 3D real-world image targets. The experimental results show that the research method can accurately reconstruct three-dimensional real-life buildings with lower reconstruction errors.