Work

Kinetic Expansion of Linear Structural Elements: A Hybrid Method for Floorplan Reconstruction From Indoor Scene Point Cloud

Year: 2025

Type: article

Abstract: Indoor floorplans are widely used in fields like Building Information Modeling (BIM), indoor navigation, emergency response, smart buildings, and architectural design simulation. However, reconstructing accurate floorplans from indoor laser point clouds is challenging due to indoor structures' complexity clutter, and occlusions. We propose KELSE, an indoor scene floorplan reconstruction method to address these challenges. We design a structural element extraction method that integrates geometric feature constraints with semantic information to identify structural elements such as walls, doors, windows, ceilings, and floors in complex indoor scenes. A kinetic data structure expansion and undirected graph optimization are then used to reconstruct the complete floorplan. Experimental results show that KELSE achieves high accuracy and completeness, with room reconstruction reaching 0.98 and 0.95, respectively. KELSE provides an efficient and precise solution for floorplan reconstruction from indoor LiDAR point cloud data.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2025.3615609

Authors: Yunlin Tu, Wenzhong Shi, Yangjie Sun, Min Zhang

Institutions: China University of Mining and Technology, Hong Kong Polytechnic University, Central South University

Language: English

Topic: 3D Surveying and Cultural Heritage

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,800

Funder: Hong Kong Polytechnic University