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Detection of Façade Regions in Street View Images from Split-and-Merge of Perspective Patches
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management. (Geospatial Informationsvetenskap)
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management. (Geospatial Informationsvetenskap)ORCID iD: 0000-0003-0085-5829
2014 (English)In: Journal of Image and Graphics, ISSN ISSN 2301-3699, Vol. 2, no 1, 8-14 p.Article in journal (Refereed) Published
Abstract [en]

Identification of building façades from digital images is one of the central problems in mobile augmented reality (MAR) applications in the built environment. Directly analyzing the whole image can increase the difficulty of façade identification due to the presence of image portions which are not façade. This paper presents an automatic approach to façade region detection given a single street view image as a pre-processing step to subsequent steps of façade identification. We devise a coarse façade region detection method based on the observation that façades are image regions with repetitive patterns containing a large amount of vertical and horizontal line segments. Firstly, scan lines are constructed from vanishing points and center points of image line segments. Hue profiles along these lines are then analyzed and used to decompose the image into rectilinear patches with similar repetitive patterns. Finally, patches are merged into larger coherent regions and the main building façade region is chosen based on the occurrence of horizontal and vertical line segments within each of the merged regions. A validation of our method showed that on average façade regions are detected in conformity with manually segmented images as ground truth.

Place, publisher, year, edition, pages
San Jose, CA, USA: Engineering and Technology Publishing , 2014. Vol. 2, no 1, 8-14 p.
Keyword [en]
façade region detection, street view image, vanishing point, mobile augmented reality
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:hig:diva-18517DOI: 10.12720/joig.2.1.8-14OAI: oai:DiVA.org:hig-18517DiVA: diva2:770876
Available from: 2014-12-11 Created: 2014-12-11 Last updated: 2015-10-06Bibliographically approved

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Liu, FeiSeipel, Stefan
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf