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Using Expert-Derived Aesthetic Attributes to Help Users in Browsing Image Databases
CONLAN, OWEN; HAMPSON, CORMAC
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.
Keyword(s): Image Retrieval; Subjectivity; Crowd Sourcing; Semantic Attributes; User exploration
Publication Date:
2011
Type: Conference item
Peer-Reviewed: Yes
Language(s): English
Institution: Trinity College Dublin
Citation(s): Cormac Hampson, Meltem Gurel, Owen Conlan, Using Expert-Derived Aesthetic Attributes to Help Users in Browsing Image Databases, 22nd International Conference on Database and Expert Systems Applications, DEXA 2011, Toulouse, France, 2011, 334 - 349
Alternative Title(s): 22nd International Conference on Database and Expert Systems Applications, DEXA 2011
First Indexed: 2014-05-13 05:21:54 Last Updated: 2015-03-23 11:36:58