The query by image content (QBIC) system
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principles of data mining
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Introduction to MPEG-7: Multimedia Content Description Interface
Introduction to MPEG-7: Multimedia Content Description Interface
Content Based Image Retrieval Using Interest Points and Texture Features
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Shape Association Based Retrieval of Infrared Satellite Images
ISM '05 Proceedings of the Seventh IEEE International Symposium on Multimedia
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Comparing global and interest point descriptors for similarity retrieval in remote sensed imagery
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Integrating gazetteers and remote sensed imagery
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
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We investigate image retrieval using interest point descriptors. New geographic information systems such as Google Earth and Microsoft Virtual Earth are providing increased access to remote sensed imagery. Content-based access to this data would support a much richer interaction than is currently possible. Interest point descriptors have proven surprisingly effective for a range of computer vision problems. We investigate their application to performing similarity retrieval in a ground-truth dataset manually constructed from 1-m IKONOS satellite imagery. We compare results of using quantized versus full descriptors, Euclidean versus Mahalanobis distance measures, and methods for comparing the sets of descriptors associated with query and target images.