Design criteria for a shape retrieval system
Computers in Industry
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
End-User Searching Challenges Indexing Practices inthe Digital Newspaper Photo Archive
Information Retrieval
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CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
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An attention-driven model for grouping similar images with image retrieval applications
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Supporting creative product/commercial design with computer-based image retrieval
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An analysis of failed queries for web image retrieval
Journal of Information Science
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Psychophysical evaluation for a qualitative semantic image categorisation and retrieval approach
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Semantic hierarchies for image annotation: A survey
Pattern Recognition
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This paper adopts the premise that the 'semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which this deficiency might be made good. Simple classifications of types of image and of types of user are proposed. Consideration is then given in outline to how semantic content is realised by each class of user within each class of image. The argument is advanced that this realisation finds expression in perceptual, generic interpretive and specific interpretive content. This analytic framework provides the basis for the specification of a broadly encompassing evaluation study, which will employ the image/user type classification and the expert domain knowledge of selected user groups in the construction of segmented test collections of real queries, images and relevance judgements. From this study should come a better-informed view on the nature of semantic information need, and on the representation and recovery of semantic content across a broad spectrum of image retrieval activity.