4-D Spatiotemporal Detection and Modeling of Free-Bending Pipelines in Cluttered 3-D Point Cloud

Analyzing free-bending pipelines in cluttered 3-D scenarios is a vital and challenging task in industrial manufacture and maintenance. It is beneficial in understanding the structure of pipelines and monitoring pipeline spacing for accurate assembly. Most existing pipeline analysis algorithms focus on regular straight pipelines and only depend on 3-D spatial cues. In this article, we propose a novel pipeline analysis framework based on 4-D spatiotemporal pipeline representation. The framework allows multiple pipeline analysis tasks ranging from detecting free-bending pipelines in point clouds and extracting 3-D skeletons to modeling complete 3-D pipelines. The 4-D pipeline representation formulates a free-bending pipeline as a 3-D cylinder sequence and incorporates 3-D spatial geometrization of each cylinder frame into temporal continuity of the frames. The multitask pipeline analysis starts from a cylinder patch and is performed on sequential pipeline frames using spatiotemporal cues. Finally, surface registration-based optimization refines pipeline skeletons, detected point cloud, and generated complete models simultaneously. The proposed algorithm is verified on real pipeline scenarios. It can deal with challenging free-bending pipeline shapes, clutter, and occlusions. Compared with existing algorithms, our algorithm achieves more comprehensive tasks and higher detection performance. The modeling of complete pipelines reaches an overall accuracy of 0.33 mm. Finally, we present a thorough analysis concerning the applicability of our algorithm from multiple aspects.