Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based query of image databases: inspirations from text retrieval
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Benchmarking Multimedia Databases
Multimedia Tools and Applications
Benchmarking for Content-Based Visual Information Search
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
The Truth about Corel - Evaluation in Image Retrieval
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Report on CLEF-2001 Experiments: Effective Combined Query-Translation Approach
CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
Combining Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Gabor Space and the Developement of Preattentive Similarity
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Strategies for Positive and Negative Relevance Feedback in Image Retrieval
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
FIRE in ImageCLEF 2005: combining content-based image retrieval with textual information retrieval
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
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The ImageCLEF task of CLEF has a main goal in the retrieval of images from multi–lingual collections. The 2003 imageCLEF saw no group using the visual information of images, which is inherently language independent. The query topics of the St. Andrews collection are defined in a way that makes visual retrieval hard as visual similarity plays a marginal role whereas semantics and background knowledge are extremely important, which can only be obtained from text. This article describes the submission of an entirely visual result. It also proposes improvements for visual retrieval systems with the current data. Section explains possible ways to make this query task more appealing to visual retrieval research groups, explaining problems of visual retrieval and what The task can do to overcome present problems. A benchmarking event is needed for visual information retrieval to remove barriers in performance. ImageCLEF can be this event and identify areas where visual retrieval might be better than textual and vice–versa. The combination of visual and textual features is an important field where research is needed.