LiveMaps: Learning Geo-Intent from Images of Maps on a Large Scale

Image search is a popular application on web search engines. Issuing a location-related query on an image search engine often returns multiple images of maps among the top ranked results. Traditionally, clicking on such images either opens the image in a new browser tab or takes users to a web page containing the image. However, finding the area of intent on an interactive web map (e.g., Bing Maps) is a manual process. In this paper, we describe a novel system, LiveMaps, for analyzing and retrieving an appropriate map viewport for a given image of a map. This provides annotation of images of maps returned by image search engines, allowing users to directly open a link to an interactive map centered on the location of interest. LiveMaps works in several stages. It first checks whether the input image represents a map. If yes, then the system attempts to identify what geographical area this map image represents. In the process, we use textual as well as visual information extracted from the image. Finally, we construct an interactive map object capturing the geographical area inferred for the image. Evaluation results on a dataset of labeled map images indicate our system constructs precise map representations while also achieving good levels of coverage.