Geo-referenced Tourist Attraction Photo Tagging by Mining Community Photo Collections

摘要

The advent of photo sharing sites like Flickr has drastically increased the volume of community photo collections on the web. Also the rising popularity of the mobile devices with GPS cameras like iPhone has made most of the photos geo-tagged. These provide new opportunities for automatically tagging the geo-referenced photos such as the tourist attraction photos. In this paper, we propose a framework for automatically tagging geo-referenced tourist attraction photos through mining the community photo collections. The photos collected from social sites are first clustered by fusing several modalities such as GPS and visual features, and then the tags of each cluster are extracted via a simple TF-IDF weighted voting scheme. Finally, for a tourist attraction photo taken with a GPS camera, it is annotated by the tags of the best matched cluster. We download a lot of photos located around some places of interest in Beijing from Flickr and manually construct a geo-referenced photo dataset. Experiment on the dataset shows an overall good performance.