Region based image annotation through multiple-instance learning
Proceedings of the 13th annual ACM international conference on Multimedia
Typicality ranking via semi-supervised multiple-instance learning
Proceedings of the 15th international conference on Multimedia
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A novel automatic image annotation (AIA) scheme is proposed based on multiple-instance learning (MIL). For a given concept, manifold ranking (MR) is first employed to MIL (referred as MR-MIL) for effectively mining the positive instances (i.e. regions in images) embedded in the positive bags (i.e. images). With the mined positive instances, the semantic model of the concept is built by the probabilistic output of SVM classifier. The experimental results reveal that high annotation accuracy can be achieved at region-level.