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Wall extraction and room detection for multi-unit architectural floor plans

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dc.contributor.author Cabrera Vargas, Dany Alejandro
dc.date.accessioned 2018-09-28T20:40:08Z
dc.date.available 2018-09-28T20:40:08Z
dc.date.copyright 2018 en_US
dc.date.issued 2018-09-28
dc.identifier.uri https://dspace.library.uvic.ca//handle/1828/10111
dc.description.abstract In the context of urban buildings, architectural floor plans describe a building's structure and spatial distribution. These digital documents are usually shared in file formats that discard the semantic information related to walls and rooms. This work proposes a new method to recover the structural information by extracting walls and detecting rooms in 2D floor plan images, aimed at multi-unit floor plans which present challenges of higher complexity than previous works. Our proposed approach is able to handle overlapped floor plan elements, notation variations and defects in the input image, and its speed makes it suitable for real applications on both desktop and mobile devices. We evaluate our methods in terms of precision and recall against our own annotated dataset of multi-unit floor plans. en_US
dc.language English eng
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject architectural floor plans en_US
dc.subject wall extraction en_US
dc.subject room detection en_US
dc.subject vectorization en_US
dc.title Wall extraction and room detection for multi-unit architectural floor plans en_US
dc.type Thesis en_US
dc.contributor.supervisor Branzan Albu, Alexandra
dc.degree.department Department of Computer Science en_US
dc.degree.level Master of Science M.Sc. en_US
dc.description.scholarlevel Graduate en_US


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