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Simplification of polygons from point cloud data for automated floorplan generation
Citation Link: https://doi.org/10.15480/882.13546
Publikationstyp
Conference Paper
Date Issued
2024-09-18
Sprache
English
Author(s)
TORE-DOI
Start Page
268
End Page
275
Citation
35. Forum Bauinformatik, fbi 2024: 268-275
Contribution to Conference
Publisher
Technische Universität Hamburg, Institut für Digitales und Autonomes Bauen
Peer Reviewed
true
This paper investigates methodologies for identifying significant edges in polygons, with a particular focus on applications in floor plan analysis. The primary objective is to develop and evaluate an algorithm that can accurately simplify and refine polygonal representations of rooms, ensuring that key structural details are preserved. The study introduces a novel simplification algorithm that combines holistic filtering, regression techniques, and a mechanism for closing polygons. This algorithm is designed to address the shortcomings of existing methods by providing a more comprehensive approach to reducing complexity while maintaining essential geometric features. The algorithm is validated through testing on two datasets of floor plans derived from real laser scans. The findings contribute to the field of automated floor plan generation, offering a scale-independent solution for simplifying redundant polygonal data while preserving spatial accuracy.
Subjects
automated floorplan generation
indoor environment
polygon simplification
scan-to-BIM
DDC Class
510: Mathematics
004: Computer Sciences
710: Landscaping, Area Planning
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Simplification of Polygons from Point Cloud Data for Automated Floorplan Generation.pdf
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