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.
|Journal||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|State||Published - 2004|
|Event||Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004 - Washington, DC, United States|
Duration: 27 Jun 2004 → 2 Jul 2004