Pipeline Extraction

Abstract

In this thesis we present an algorithm that detects and models pipelines in 3-dimensional point clouds. The algorithm starts from a user provided seed and alternates between model building and primitive detection as it tracks the pipeline. The algorithm does not require preprocessing such as registration or subsampling. When provided with a suitable seed and search area size the algorithm produces good models.