Automatic 3D industrial point cloud modeling and recognition

3D modeling of point clouds is an important but time-consuming process, inspiring extensive research in automatic methods. Prior efforts focus on primitive geometry, street structures or indoor objects, but industrial data has rarely been pursued. Our work presents a method for automatic modeling and recognition of 3D industrial site point clouds, dividing the task into 3 separate sub-problems: pipe modeling, plane classification, and object recognition. The results are integrated to obtain the complete model, revealing some issues during the integration, solved by utilizing information gained from each individual process. Experiments show that the presented method automatically models large and complex industrial scenes with a quality that outperforms leading commercial modeling software and is comparable to professional hand-made models.