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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© 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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