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This paper presents contextual kernel and spectral methods for learning the semantics of images that allow us to automatically annotate an image with keywords. First, to exploit the context of visual words within images for automatic image annotation, we define a novel spatial string kernel to quantify the similarity
Social bookmarking tools are rapidly emerging on the Web as it can be witnessed by the overwhelming number of participants. In such spaces, users annotate resources by means of any keyword or tag that they find relevant, giving raise to lightweight conceptual structures aka folksonomies. In this respect, needless to
The LIGVID system is designed for online interactive video shots retrieval and annotation. It uses a user-controlled combination of multiple criteria: keywords, phonetic string, similarity to example images, semantic categories, and relevance feedback strategies: visual and temporal similarity to already identified
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