Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
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
Content-based summarization for personal image library
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Creating Efficient Codebooks for Visual Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
International Journal of Computer Vision
Content-based image retrieval by indexing random subwindows with randomized trees
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
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In this paper, we present a methodology on how to measure the visual similarity between a query image and hierarchically represented image databases for content based image retrieval. The images in database are hierarchically summarized and classified by recovered extrinsic camera parameters as well as constrained agglomerative clustering methods. The constrained agglomerative hierarchical image clustering method whose strategy is to extract a multi-level partitioning and grouping of multiple images is used for balancing the hierarchical trees and summarization. The visual codebooks which are hierarchically quantized in the clusters are used to calculate the similarity measure with a query image's visual features. Our proposed visual similarity measure and summarization of image data provide a very efficient way for searching and retrieving the images that have similar visual contents and geometrical location.