POINT CLOUD ROOM SEGMENTATION BASED ON INDOOR SPACES AND 3D MATHEMATICAL MORPHOLOGY

Room segmentation is a matter of ongoing interesting for indoor navigation and reconstruction in robotics and AEC. While in robotics field, the problem room segmentation has been typically addressed on 2D floorplan, interest in enrichment 3D models providing more detailed representation of indoors h...

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Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XLIV-4/W1-2020; pp. 49 - 55
Main Authors: Frías, E., Balado, J., Díaz-Vilariño, L., Lorenzo, H.
Format: Journal Article Conference Proceeding
Language:English
Published: Gottingen Copernicus GmbH 03.09.2020
Copernicus Publications
Subjects:
Algorithms
Dilation
Floorplans
Image reconstruction
Image segmentation
Indoor environments
Mathematical analysis
Mathematical morphology
Morphology
Navigation
Robotics
Three dimensional models
Two dimensional models
ISSN:2194-9034, 1682-1750, 2194-9034
Online Access:Get full text
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Summary:Room segmentation is a matter of ongoing interesting for indoor navigation and reconstruction in robotics and AEC. While in robotics field, the problem room segmentation has been typically addressed on 2D floorplan, interest in enrichment 3D models providing more detailed representation of indoors has been growing in the AEC. Point clouds make available more realistic and update but room segmentation from point clouds is still a challenging topic. This work presents a method to carried out point cloud segmentation into rooms based on 3D mathematical morphological operations. First, the input point cloud is voxelized and indoor empty voxels are extracted by CropHull algorithm. Then, a morphological erosion is performed on the 3D image of indoor empty voxels in order to break connectivity between voxels belonging to adjacent rooms. Remaining voxels after erosion are clustered by a 3D connected components algorithm so that each room is individualized. Room morphology is retrieved by individual 3D morphological dilation on clustered voxels. Finally, unlabelled occupied voxels are classified according proximity to labelled empty voxels after dilation operation. The method was tested in two real cases and segmentation performance was evaluated with encouraging results.
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ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLIV-4-W1-2020-49-2020