Data processing: artificial intelligence – Knowledge processing system
Reexamination Certificate
2007-01-24
2010-10-12
Vincent, David R (Department: 2129)
Data processing: artificial intelligence
Knowledge processing system
Reexamination Certificate
active
07814040
ABSTRACT:
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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Zhang Ruofei
Zhang Zhongfei
Hoffberg Steven H.
Ostrolenk Faber LLP
The Research Foundation of State University of New York
Vincent David R
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