A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation

This paper presents a framework to address the challenges involved in building point cloud cleaning, plane detection, and semantic segmentation, with the ultimate goal of enhancing building modeling. We focus in the cleaning stage on removing outliers from the acquired point cloud data by employing an adaptive threshold technique based on z-score measure. Following the cleaning process, we perform plane detection using the robust RANSAC paradigm. The goal is to carry out multiple plane segmentations, and to classify segments into …

acquired building challenges cleaning cloud cloud data cs.cv data detection focus framework modeling outliers paper plane segmentation semantic stage threshold