The starting point of ancient architecture digitization and 3D reconstruction research is data acquisition. Thus, this paper mainly analyzes the processing of 3D laser scanning data and the construction accuracy of 3D reconstruction models of ancient buildings based on point cloud data. This paper discusses the basic theory of point cloud data and the preprocessing of point cloud data, including point cloud splicing, point cloud denoising, point cloud streamlining, point cloud segmentation, and other methods and applicability are discussed in detail. The boundary extraction algorithm based on RANSAC and the graph cut algorithm are utilized to obtain the main frame line of the building, and a proposed method for reconstruction based on multi-view projection is proposed. Classify laser point cloud samples from ancient buildings, calculate each wall color’s R, G, and B values, and obtain preliminary classifications of laser point cloud data categories. The RANSAC algorithm was used to extract the point cloud data plane extraction peak of the ancient tower building, combined with the three-dimensional modeling coordinate difference of the test points, to analyze the accuracy of the three-dimensional modeling technology of ancient buildings in this paper. The number of plane extraction points of the RANSAC algorithm is 9504, and the standard deviation is 0.0505, which is close to 0. The results are more accurate, and the extraction effect has a certain degree of superiority. The plane coordinate deviation of the reconstruction model of the ancient tower is mainly concentrated in the range of 0.10~0.40m, and the individual coordinate difference is more than 0.10m. The errors in the x -direction and y -direction are ±0.18m and ±0.23m, respectively, and it can be seen from the results of the error calculation that the three-dimensional reconstruction plan of the building proposed in this paper can complete the reconstruction of the three-dimensional model of the building with a high degree of accuracy.