MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Color Image Retrieval Based on Primitives of Color Moments
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Semantics In Digital Photos: A Contenxtual Analysis
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Real time google and live image search re-ranking
MM '08 Proceedings of the 16th ACM international conference on Multimedia
ICSC '10 Proceedings of the 2010 IEEE Fourth International Conference on Semantic Computing
Surveying the reality of semantic image retrieval
VISUAL'05 Proceedings of the 8th international conference on Visual Information and Information Systems
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Image repositories often contain a large amount of metadata about their content. However many resources, such as photographs, have inherent aesthetic qualities that can be difficult to describe in a semantically consistent and usable manner, yet would be highly valuable for users in exploring large image repositories, such as Flickr. Automatically augmenting existing metadata with expert perspectives has the potential to give users a consistent aesthetic vocabulary to search and explore such repositories. SARA (Semantic Attribute Reconciliation Architecture) is a system that supports users to leverage domain expertise while searching for items in a metadata-rich domain. X2Photo is a tool built on SARA's functionality to enable image searching based on a picture's aesthetic characteristics and user-generated tags. This paper describes X2Photo in detail, the approach to augmenting visual media with expertise, and the evaluation results which reveal how semantically described aesthetics can support complementary search axes for image retrieval.