Searching the web with mobile images for location recognition

Tom Yeh, Konrad Tollmar, Trevor Darrell

Research output: Contribution to journalConference articlepeer-review

105 Scopus citations


In this paper, we describe an approach to recognizing location from mobile devices using image-based web search. We demonstrate the usefulness of common image search metrics applied on images captured with a camera-equipped mobile device to find matching images on the World Wide Web or other general-purpose databases. Searching the entire web can be computationally overwhelming, so we devise a hybrid image-and-keyword searching technique. First, image-search is performed over images and links to their source web pages in a database that indexes only a small fraction of the web. Then, relevant keywords on these web pages are automatically identified and submitted to an existing text-based search engine (e.g. Google) that indexes a much larger portion of the web. Finally, the resulting image set is filtered to retain images close to the original query. It is thus possible to efficiently search hundreds of millions of images that are not only textually related but also visually relevant. We demonstrate our approach on an application allowing users to browse web pages matching the image of a nearby location.

Original languageEnglish
Pages (from-to)II76-II81
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
StatePublished - 2004
EventProceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004 - Washington, DC, United States
Duration: 27 Jun 20042 Jul 2004


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