Geospatial Web Image Mining

One commonly asked question when confronted with a photograph is “Where is this place?” When talking about a place mentioned on the Web, the question arises “What does this place look like?” Today, these questions can not reliably be answered forWeb images as they typically do not reveal their relationship to an actual geographic position. Analysis of the keywords surrounding the images or the content of the images alone has not yet achieved results that would allow deriving a precise location information to select representative images. Photos that are reliably tagged with labels of place names or areas only cover a small fraction of available images and also remain at a keyword level.

Results can be improved for arbitrary Web images by combining features from the Web page as image context and the images themselves as content. We propose a location-based search for Web images that allows finding images that are only implicitly related to a geographic position without having to rely on explicit tagging or metadata. Our spatial Web image search engine first crawls and identifies location-related information on Web pages to determine a geographic relation of the Web page, and then extends this geospatial reference further to assess an image’s location. Combining context and content analysis, we are able to determine if the image actually is a realistic representative photograph of a place and related to a geographic position.

Keywords: Image Retrieval, Geospatial Search, Semantic Retrieval, Multimedia Retrieval, Image Analysis, Web Search, Geographic Web Information Retrieval, Context Analysis, Location Assessment, Location Classification, Photo Annotation