ABSTRACT
In recent years, with the aim of improving the efficiency of maintenance, utilization of 3D models in bridge management has been catching attention. To utilize 3D models for bridge management, it is important to establish the method to construct them. It takes a lot of work to manually create an accurate 3D model from construction drawings. Under such circumstances, there has been lots of research in which they construct 3D models using various data, including construction drawings and point cloud data. However, there are some problems like the difficulty of applying their method to the vast number of existing bridges. In this research, the authors propose a 3D model construction method using neural network which learned generic shapes of bridge parts. In particular, the authors propose a method to extract latent information from point cloud data by introducing structured knowledge into network calculations and use it to construct 3D models.
