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Automatic structural scene digitalization

In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and...

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Detalles Bibliográficos
Autores principales: Tang, Rui, Wang, Yuhan, Cosker, Darren, Li, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5693441/
https://www.ncbi.nlm.nih.gov/pubmed/29149206
http://dx.doi.org/10.1371/journal.pone.0187513
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author Tang, Rui
Wang, Yuhan
Cosker, Darren
Li, Wenbin
author_facet Tang, Rui
Wang, Yuhan
Cosker, Darren
Li, Wenbin
author_sort Tang, Rui
collection PubMed
description In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and other ambiguous assets. Technically, a general rule-based filter parsing method is fist adopted to extract effective information from the original floor plan. Then, an image-processing based recovery method is employed to correct information extracted in the first step. Our proposed method is fully automatic and real-time. Such analysis system provides high accuracy and is also evaluated on a public website that, on average, archives more than ten thousands effective uses per day and reaches a relatively high satisfaction rate.
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spelling pubmed-56934412017-11-30 Automatic structural scene digitalization Tang, Rui Wang, Yuhan Cosker, Darren Li, Wenbin PLoS One Research Article In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and other ambiguous assets. Technically, a general rule-based filter parsing method is fist adopted to extract effective information from the original floor plan. Then, an image-processing based recovery method is employed to correct information extracted in the first step. Our proposed method is fully automatic and real-time. Such analysis system provides high accuracy and is also evaluated on a public website that, on average, archives more than ten thousands effective uses per day and reaches a relatively high satisfaction rate. Public Library of Science 2017-11-17 /pmc/articles/PMC5693441/ /pubmed/29149206 http://dx.doi.org/10.1371/journal.pone.0187513 Text en © 2017 Tang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tang, Rui
Wang, Yuhan
Cosker, Darren
Li, Wenbin
Automatic structural scene digitalization
title Automatic structural scene digitalization
title_full Automatic structural scene digitalization
title_fullStr Automatic structural scene digitalization
title_full_unstemmed Automatic structural scene digitalization
title_short Automatic structural scene digitalization
title_sort automatic structural scene digitalization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5693441/
https://www.ncbi.nlm.nih.gov/pubmed/29149206
http://dx.doi.org/10.1371/journal.pone.0187513
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