EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
AI Magazine
Image retrieval using a multilingual ontology
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Fusion of face and speech data for person identity verification
IEEE Transactions on Neural Networks
Image Sense Classification in Text-Based Image Retrieval
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
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For a computer to recognize objects, persons, situations or actions in multimedia, it needs to have learned models of each thing beforehand. For the moment, no large, general collection of training examples exists for the wide variety of things that we would want to automatically recognize in multimedia, video and still images. We believe that the WWW and current technology can allow us to automatically build such a resource. This paper describes a methodology for the construction of a grounded, general purpose, multimedia ontology that is instantiated through web processing. In this hierarchically organized ontology, concepts corresponding to concrete objects, persons, situations and actions are linked with still images, videos and sounds that represent exemplars of each concept. These examples are necessary resources for computing discriminating signatures for the recognition of the concepts in still images or videos. Since images retrieved using existing image search engines contain much noise hand are not always representative, we also present here our methodology for finding good representative for each concept.