A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Similarity-Based Object Retrieval Using Appearance and Geometric Feature Combination
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Modelling image semantic descriptions from web 2.0 documents using a hybrid approach
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Analyzing Ancient Maya Glyph Collections with Contextual Shape Descriptors
International Journal of Computer Vision
Interactive exhibition with ambience using video avatar and animation on huge screen
Proceedings of the 2011 international conference on Virtual and mixed reality: systems and applications - Volume Part II
Searching the past: an improved shape descriptor to retrieve maya hieroglyphs
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms, including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed, but integrated, digital collections.