Geo-tagging online videos using semantic expansion and visual analysis

Xavier Sevillano, Tomas Piatrik, Krishna Chandramouli, Qianni Zhang, Ebroul Izquierdo

Abstract: The association of geographical tags to multimedia resources enables browsing and searching online multimedia repositories using geographical criteria, but millions of already online but non geotagged videos and images remain invisible to the eyes of this type of systems. This situation calls for the development of automatic geotagging techniques capable of estimating the location where a video or image was taken. This paper presents a bimodal geo-tagging system for online videos based on extracting and expanding the geographical information contained in the textual metadata and on visual similarity criteria. The performance of the proposed system is evaluated on the MediaEval 2011 Placing task data set, and compared against the participants in that workshop.