Abstract
AbstractNowadays social media are very popular for people to share their photos with their friends. Many of the photos are geo-tagged (with GPS information) whether automatically or manually. Social media management websites such as Flickr allow users manually labeling their uploaded photos with GPS with the interface of dragging them into the map. However, manually dragging the photos to the map will bring more error and very boring for users to labeling their photos. Thus in this paper, a GPS location estimation approach is proposed. For an uploaded image, its GPS information is estimated by both hierarchical global feature classification and local feature refinement to guarantee the accuracy and computational cost. To guarantee the estimation performances, k-nearest neighbors are selected in global feature classification stage. Experiments show the effectiveness of our proposed approach.KeywordsGPS EstimationK-NNHierarchical StructureBoWGeo-tag
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