Content-Based Image Annotation Refinement

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Content-Based Image Annotation Refinement
Automatic image annotation has been an active research topic due to its great importance in image retrieval and management. However, results of the state-of-the-art image annotation methods are often unsatisfactory. Despite continuous efforts in inventing new annotation algorithms, it would be advantageous to develop a dedicated approach that could refine imprecise annotations. In this paper, a novel approach to automatically refining the original annotations of images is proposed. For a query image, an existing image annotation method is first employed to obtain a set of candidate annotations. Then, the candidate annotations are re-ranked and only the top ones are reserved as the final annotations. By formulating the annotation refinement process as a Markov process and defining the candidate annotations as the states of a Markov chain, a content-based image annotation refinement (CIAR) algorithm is proposed to re-rank the candidate annotations. It leverages both corpus information a...
Changhu Wang, Feng Jing, Lei Zhang, Hong-Jiang Zha
Added 02 Jun 2010
Updated 02 Jun 2010
Type Conference
Year 2007
Where CVPR
Authors Changhu Wang, Feng Jing, Lei Zhang, Hong-Jiang Zhang
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