Comparing discriminating transformations and SVM for learning during multimedia retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Efficient Matching and Indexing of Graph Models in Content-Based Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
ImageGrouper: Search, Annotate and Organize Images by Groups
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Unsupervised Image Clustering Using the Information Bottleneck Method
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Document Image Recognition Based on Template Matching of Component Block Projections
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Journal of Machine Learning Research
Index-driven similarity search in metric spaces (Survey Article)
ACM Transactions on Database Systems (TODS)
Journal of the American Society for Information Science and Technology
Hierarchical structures for video query systems
dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
Enhancing relevance feedback in image retrieval using unlabeled data
ACM Transactions on Information Systems (TOIS)
Visual guided navigation for image retrieval
Pattern Recognition
Interactive high-dimensional index for large Chinese calligraphic character databases
ACM Transactions on Asian Language Information Processing (TALIP)
Deriving semantics for image clustering from accumulated user feedbacks
Proceedings of the 15th international conference on Multimedia
A survey of browsing models for content based image retrieval
Multimedia Tools and Applications
Navidgator - Similarity Based Browsing for Image and Video Databases
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Group-based interface for content-based image retrieval
Proceedings of the Working Conference on Advanced Visual Interfaces
A Multi-class Kernel Alignment Method for Image Collection Summarization
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Towards optimal indexing for relevance feedback in large image databases
IEEE Transactions on Image Processing
A next generation browsing environment for large image repositories
Multimedia Tools and Applications
Image databases browsing by unsupervised learning
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Extended papers from NPAR 2010: Stylized ambient displays of digital media collections
Computers and Graphics
A latent image semantic indexing scheme for image retrieval on the web
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Unsupervised clustering in personal photo collections
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
Interacting with image collections: visualisation and browsing of image repositories
Proceedings of the 20th ACM international conference on Multimedia
A kernel-based framework for image collection exploration
Journal of Visual Languages and Computing
Interactive exploration of image collections on mobile devices
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Generation of web recommendations using implicit user feedback and normalised mutual information
International Journal of Knowledge and Web Intelligence
| Hi-index | 0.01 |
The advent of large image databases (>10000) has created a need for tools which can search and organize images automatically by their content. This paper focuses on the use of hierarchical tree-structures to both speed-up search-by-query and organize databases for effective browsing. The first part of this paper develops a fast search algorithm based on best-first branch and bound search. This algorithm is designed so that speed and accuracy may be continuously traded-off through the selection of a parameter λ. We find that the algorithm is most effective when used to perform an approximate search, where it can typically reduce computation by a factor of 20-40 for accuracies ranging from 80% to 90%. We then present a method for designing a hierarchical browsing environment which we call a similarity pyramid. The similarity pyramid groups similar images together while allowing users to view the database at varying levels of resolution. We show that the similarity pyramid is best constructed using agglomerative (bottom up) clustering methods, and present a fast sparse clustering method which dramatically reduces both memory and computation over conventional methods