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Automatic Image Annotation with Cooperation of Concept-Specific and Universal Visual Vocabularies
[chapter]
2010
Lecture Notes in Computer Science
This paper proposes an automatic image annotation method based on concept-specific image representation and discriminative learning. Firstly, the concept-specific visual vocabularies are generated by assuming that localized features from the images with a specific concept are of the distribution of Gaussian Mixture Model (GMM). Each component in the GMM is taken as a visual token of the concept. The visual tokens of all the concepts are clustered to obtain a universal token set. Secondly, the
doi:10.1007/978-3-642-11301-7_28
fatcat:pwzfni3scfebvauxsvneevy55u