Aiming at the limitation of using a single data source for 3D reconstruction,this paper combines heterogeneous tilt images and 3D laser point cloud for 3D real scene reconstruction.In the preliminary work,the initial model of the campus library was established by using oblique photography technology to generate image point clouds,and its facade data was acquired by using a three-dimensional laser scanner to complete the preprocessing work such as denoising and splicing.For the registration of preprocessed image point cloud and laser point cloud data,firstly,the principal component analysis method is used to reduce the dimension of the data,align the pose direction of the cross-source point cloud,and obtain the initial pose by using the spatial geometric center matching of the data.Then,TrICP algorithm is used to complete the accurate registration of the cross-source point cloud with low overlap rate.The experimental results show that the accuracy of the coarse registration method in this paper is up to 0.32 m,which is much higher than that of the fast point feature histogram algorithm.In the precision analysis of precise registration,the independent precision of the building facade is 0.03 m,0.08 m,0.22 m,and the overall precision reaches 0.08 m,which is 53.5 % higher than the traditional ICP algorithm.