Abstract
Buildings plays a very important role in the development of culture, art, history, and in our daily life. If we can retrieve unique features for describing a building, it might have some helps for architecture history, digital resources of architecture, even for determining the position of a person in the urban area. As the popularity of smart mobile devices, if we could have some interesting application for getting information of buildings around user, by captured building images in any direction and view, it will be a great help for the promotion of culture and tourism industry. In this paper, we propose a preliminary building recognition system using the SURF and color features for distinctive buildings in a city. This system using Google Street View’s images as a feature learning database. Based on the research of buildings’ characteristics in a modern city, the recognition system can identify buildings efficiently in different scales, rotation, and partial occlusion of the building’s image in this system.
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References
Hu J, Sawyer J, Herve JY (2006) Building detection and recognition for an automated tour guide. In: IEEE international conference on systems, man and cybernetics, pp 283–289
Lim B, Kim J (2009) Efficient database reduction method of building recognition using global positioning system on mobile device. In: IEEE international symposium on wireless pervasive computing, pp 1–5
Levitt S, Aghdasi F (1997) Texture measures for building recognition in aerial photographs. In: Proceedings of south African symposium on communications and signal processing, pp 75–80
Michaelsen E, FGAN-FOM, Ettlingen, Doktorski L, Soergel U, Stilla U (2007) Perceptual grouping for building recognition in high-resolution SAR images using the GESTALT-system. In: IEEE urban remote sensing joint event, pp 1–6
Chung YC, Han TX, He Z (2009) Building recognition using sketch-based representations and spectral graph matching. In: International conference on computer vision, pp 2014–2020
Zhang W, Kosecka J (2005) Localization based on building recognition. In: Computer society conference on computer vision and pattern recognition, p 21
Shao TSH, Gool LV (2003) Zurich buildings database for image based recognition. In: Technical report no. 260. Swiss Federal Institute of Technology, May 2003
Bay H, Tuytelaars T, Van Gool L (2006) SURF: speeded up robust features. In: Proceedings of European conference on computer vision, pp 404–417
Juan L, Gwun O (2009) A comparison of SIFT, PCA-SIFT and SURF. Int J Image Process 3:143–152
Google Streetview Static API. http://jamiethompson.co.uk/web/2010/05/15/google-streetview-static-api/
Open SURF. http://www.chrisevansdev.com/computer-vision-opensurf.html
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© 2013 Springer Science+Business Media Dordrecht
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Chen, SW., Chung, YH., Chien, HF., Chang, CW. (2013). A SURF Feature Based Building Recognition System for Distinctive Architectures. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_12
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DOI: https://doi.org/10.1007/978-94-007-6996-0_12
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