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Semantic Segmentation and Reconstruction of Indoor Scene Point CloudsHAO, W.   , WEI, H. , WANG, Y. |
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Author keywords
point clouds, semantic segmentation, indoor scene reconstruction, slicing-projection method, template matching
References keywords
point(28), vision(15), clouds(14), semantic(13), reconstruction(13), recognition(13), indoor(13), segmentation(12), cloud(12), pattern(11)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2024-08-31
Volume 24, Issue 3, Year 2024, On page(s): 3 - 12
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.03001
Web of Science Accession Number: 001306111400001
SCOPUS ID: 85203023424
Abstract
Automatic 3D reconstruction of indoor scenes remains a challenging task due to the incomplete and noisy nature of scanned data. We propose a semantic-guided method for reconstructing indoor scene based on semantic segmentation of point clouds. Firstly, a Multi-Feature Adaptive Aggregation Network is designed for semantic segmentation, assigning the semantic label for each point. Then, a novel slicing-projection method is proposed to segment and reconstruct the walls. Next, a hierarchical Euclidean Clustering is proposed to separate objects into individual ones. Finally, each object is replaced with the most similar CAD model from the database, utilizing the Rotational Projection Statistics (RoPS) descriptor and the iterative closest point (ICP) algorithm. The selected template models are then deformed and transformed to fit the objects in the scene. Experimental results demonstrate that the proposed method achieves high-quality reconstruction even when faced with defective scanned point clouds. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
