The virtual indoor scene is reconstructed by building a virtual indoor scene, and a virtual indoor scene construction technology based on lidar point cloud data is proposed. The lidar point cloud data is collected by using a three-dimensional optical surface scanning device, and the lidar point cloud data of the virtual indoor scene is filtered by using a fusion Kalman filtering method to reduce the interference of the point cloud data, extract the spatial distribu- tion domain features of the virtual indoor scene, and obtain the global mark points of the measured objects in the virtual indoor scene. Through reverse design and reconstruction of 3D boundary contour feature points, the scattered point cloud of virtual indoor scene is reconstructed and sparse feature points are fitted, and the virtual indoor scene is recon- structed by texture rendering on the fitting surface. The simulation results show that the lidar point cloud data recon- structed by this method is better, and the feature information of the original point cloud is more abundant, which can meet the needs of better reconstruction geometric accuracy, the reconstruction accuracy reached 0. 98, and the recon- struction efficiency reached 4. 5 h.