Incentive Based Image Annotation
نویسندگان
چکیده
In this paper, we present a novel annotation paradigm with an emphasis on two facets – (a) semantic propagation and (b) an end user experience that provides insight. We attempt to propagate semantics of the annotations, by using WordNet, and low-level features extracted from the images. We introduce novel semantic dissimilarity measures, and propagation frameworks. The system also provides insight to the user, by providing her with knowledge sources that are constrained by the user and media context. The knowledge sources are presented using context-aware hypermediation. Our Experimental results indicate that the system performs well. The semantic propagation results are good – we converge close to the semantics of the image by annotating a small number (~15%) of database images.
منابع مشابه
Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models
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