Video parsing, retrieval and browsing: an integrated and content-based solution
Proceedings of the third ACM international conference on Multimedia
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
International Journal of Computer Vision
ViewFocus: explore places of interests on Google maps using photos with view direction filtering
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Searching the web with mobile images for location recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
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In this paper, we propose a new image-based algorithm to identify where a tourist is when visiting unfamiliar places. When the tourist takes a photo of an unfamiliar place, our algorithm can recognize where the tourist is by retrieving similar images from an image database, where location information is associated with each image. Our method is not only fusing global and local information but using a coarse-to-fine three-stage search process. We first extract image descriptors from the image taken by the tourist and retrieve a number of most relevant images from the database. Then, we re-rank these relevant images based on geometric consistency. Finally, our method determines where the tourist is by using an image-to-class distance measure. Promising performance of the proposed algorithm is demonstrated by the experiments.