Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
World-scale mining of objects and events from community photo collections
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Boosting image retrieval through aggregating search results based on visual annotations
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Object Mining Using a Matching Graph on Very Large Image Collections
ICVGIP '08 Proceedings of the 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing
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On the web, tagging is the preferred approach to describing multimedia items in order to make them searchable. The information value of tags can be significantly enhanced if they are linked to specific image regions. In this paper, we describe an approach to automatically detect regions of interest (ROIs) that are visually related to a given tag. Our technique is domain independent and works unsupervised, just by leveraging the knowledge from large-scale collections of tagged images. The ROIs are obtained by local feature matching between similarly tagged images. We demonstrate the performance and high accuracy of our approach in experiments on a set of 41 different topics and more than 9000 images.