Automatic image annotation using semantic relevance
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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Automatic image annotation (AIA) is an effective technology for improving the image retrieval. In this paper, a novel annotation scheme based on neural network (NN) is first proposed for characterizing the hidden association between two modalities, i.e. the visual and the textual modalities. Furthermore, latent semantic analysis (LSA) is employed to the NN based annotation scheme (noted as LSA-NN) for discovering the latent contextual correlation among the keywords, which is neglected by many previous annotation methods. Instead of region-level as most previous works do, the LSA-NN based annotation scheme is built at image-level to avoid the prior image segmentation. The experimental results reveal that the high annotation accuracy can be achieved at image-level.