Fast 3D reconstruction of ancient buildings based on virtual reality and convolution network

Abstract

With the rapid development of virtual reality and convolutional network technology in the field of computer vision, enabling deep learning technology to 3D reconstruction has become a research hotspot. 3D reconstruction based on virtual reality and convolutional networks is widely used in the field of 3D reconstruction of ancient buildings. This paper studies the 3D reconstruction of ancient buildings based on virtual reality and convolutional network technology. Firstly, the principle of 3D reconstruction and the method framework for fast reconstruction of ancient models are introduced. Then, on the basis of semantic segmentation of 2D images, the segmented image blocks of indoor scene elements are extracted, and the 3D model matching model of convolutional neural network is analyzed. 3D technology plays a very important role in the reconstruction of ancient buildings.