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System and method for image annotation and multi-modal image retrieval using probabilistic semantic models comprising at least one joint probability distribution
System and method for image annotation and multi-modal image retrieval using probabilistic semantic models comprising at least one joint probability distribution
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机译:使用包括至少一个联合概率分布的概率语义模型进行图像注释和多模态图像检索的系统和方法
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摘要
Systems and Methods for multi-modal or multimedia image retrieval are provided. Automatic image annotation is achieved based on a probabilistic semantic model in which visual features and textual words are connected via a hidden layer comprising the semantic concepts to be discovered, to explicitly exploit the synergy between the two modalities. The association of visual features and textual words is determined in a Bayesian framework to provide confidence of the association. A hidden concept layer which connects the visual feature(s) and the words is discovered by fitting a generative model to the training image and annotation words. An Expectation-Maximization (EM) based iterative learning procedure determines the conditional probabilities of the visual features and the textual words given a hidden concept class. Based on the discovered hidden concept layer and the corresponding conditional probabilities, the image annotation and the text-to-image retrieval are performed using the Bayesian framework.
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