Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPRW.2009.5206749
Title: Tour the World: Building a web-scale landmark recognition engine
Authors: Zheng, Y.-T.
Zhao, M.
Song, Y.
Adam, H.
Buddemeier, U.
Bissacco, A.
Brucher, F.
Chua, T.-S. 
Neven, H.
Issue Date: 2009
Source: Zheng, Y.-T.,Zhao, M.,Song, Y.,Adam, H.,Buddemeier, U.,Bissacco, A.,Brucher, F.,Chua, T.-S.,Neven, H. (2009). Tour the World: Building a web-scale landmark recognition engine. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 : 1085-1092. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPRW.2009.5206749
Abstract: Modeling and recognizing landmarks at world-scale is a useful yet challenging task. There exists no readily available list of worldwide landmarks. Obtaining reliable visual models for each landmark can also pose problems, and efficiency is another challenge for such a large scale system. This paper leverages the vast amount of multimedia data on the web, the availability of an Internet image search engine, and advances in object recognition and clustering techniques, to address these issues. First, a comprehensive list of landmarks is mined from two sources: (1) ∼20 million GPS-tagged photos and (2) online tour guide web pages. Candidate images for each landmark are then obtained from photo sharing websites or by querying an image search engine. Second, landmark visual models are built by pruning candidate images using efficient image matching and unsupervised clustering techniques. Finally, the landmarks and their visual models are validated by checking authorship of their member images. The resulting landmark recognition engine incorporates 5312 landmarks from 1259 cities in 144 countries. The experiments demonstrate that the engine can deliver satisfactory recognition performance with high efficiency. © 2009 IEEE.
Source Title: 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/42169
ISBN: 9781424439935
DOI: 10.1109/CVPRW.2009.5206749
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