发明名称 |
System and method for image annotation and multi-modal image retrieval using probabilistic semantic models comprising at least one joint probability distribution |
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. |
申请公布号 |
US8204842(B1) |
申请公布日期 |
2012.06.19 |
申请号 |
US20100903099 |
申请日期 |
2010.10.12 |
申请人 |
ZHANG RUOFEI;ZHANG ZHONGFEI;THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK |
发明人 |
ZHANG RUOFEI;ZHANG ZHONGFEI |
分类号 |
G06F17/00 |
主分类号 |
G06F17/00 |
代理机构 |
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代理人 |
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地址 |
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