Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
The nature of statistical learning theory
The nature of statistical learning theory
RELIEF: combining expressiveness and rapidity into a single system
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A unified framework for semantics and feature based relevance feedback in image retrieval systems
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Explicit query formulation with visual keywords
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Symbolic photograph content-based retrieval
Proceedings of the eleventh international conference on Information and knowledge management
Unifying Keywords and Visual Contents in Image Retrieval
IEEE MultiMedia
EMIR2: An Extended Model for Image Representation and Retrieval
DEXA '95 Proceedings of the 6th International Conference on Database and Expert Systems Applications
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Multimedia Tools and Applications
A user study to investigate semantically relevant contextual information of WWW images
International Journal of Human-Computer Studies
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
Multifaceted conceptual image indexing on the world wide web
Information Processing and Management: an International Journal
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This paper presents an approach for integrating perceptual signal features (i.e. color and texture) and semantic information within a coupled architecture for image indexing and retrieval. It relies on an expressive knowledge representation formalism handling high-level image descriptions and a full-text query framework. It consequently brings the level of image retrieval closer to users' needs by translating low-level signal features to high-level conceptual data and integrate them with semantic characterization within index and query structures. Experiments on a corpus of 2500 photographs validate our approach by considering recall-precision indicators over a set of 46 full-text queries coupling high-level semantic and signal features.