Communication Systems Group

We present a hierarchical, multi-modal approach for placing Flickr videos on the map. Our approach makes use of exter-nal resources to identify toponyms in the metadata and of visual and textual features to identify similar content. First, the geographical boundaries extraction method identifies the country and its dimension. We use a database of more than 3.6 million Flickr images to group them together into geo-graphical regions and to build a hierarchical model. A fusion of visual and textual methods is used to classify the videos’ location into possible regions. Next, the visually nearest neighbour method uses a nearest neighbour approach to find correspondences with the training images within the pre-classified regions. The video sequences are represented us-ing low-level feature vectors from multiple key frames. The Flickr videos are tagged with the geo-information of the vi-sually most similar training item within the regions that is previously filtered by the pre-classification step for each test video. The results show that we are able to tag one third of our videos correctly within an error of 1 km