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. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/10111 |
| Date | 28 September 2018 |
| Creators | Cabrera Vargas, Dany Alejandro |
| Contributors | Branzan Albu, Alexandra |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | Available to the World Wide Web |
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