Machine Learning
Information Retrieval
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Mobile Vision System for Urban Detection with Informative Local Descriptors
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Object identification and retrieval from efficient image matching. Snap2Tell with the STOIC dataset
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Markerless Outdoor Localisation Based on SIFT Descriptors for Mobile Applications
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Localized Content-Based Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision Based Road Crossing Scene Recognition for Robot Localization
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 06
Portable extraction of partially structured facts from the web
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
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
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Geo-based automatic image annotation
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
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A novel solution to the challenge of automatic image annotation is described. Given an image with GPS data of its location of capture, our system returns a semantically-rich annotation comprising tags which both identify the landmark in the image, and provide an interesting fact about it, e.g. "A view of the Eiffel Tower, which was built in 1889 for an international exhibition in Paris". This exploits visual and textual web mining in combination with content-based image analysis and natural language processing. In the first stage, an input image is matched to a set of community contributed images (with keyword tags) on the basis of its GPS information and image classification techniques. The depicted landmark is inferred from the keyword tags for the matched set. The system then takes advantage of the information written about landmarks available on the web at large to extract a fact about the landmark in the image. We report component evaluation results from an implementation of our solution on a mobile device. Image localisation and matching offers 93.6% classification accuracy; the selection of appropriate tags for use in annotation performs well (F1M of 0.59), and it subsequently automatically identifies a correct toponym for use in captioning and fact extraction in 69.0% of the tested cases; finally the fact extraction returns an interesting caption in 78% of cases.