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A probabilistic semantic model for image annotation and multi-modal image retrieval

8 years 9 months ago
A probabilistic semantic model for image annotation and multi-modal image retrieval
This paper addresses automatic image annotation problem and its application to multi-modal image retrieval. The contribution of our work is three-fold. (1) We propose a probabilistic semantic model in which the visual features and the textual words are connected via a hidden layer which constitutes the semantic concepts to be discovered to explicitly exploit the synergy among the modalities. (2) The association of visual features and textual words is determined in a Bayesian framework such that the confidence of the association can be provided. (3) Extensive evaluation on a large-scale, visually and semantically diverse image collection crawled from Web is reported to evaluate the prototype system based on the model. In the proposed probabilistic model, a hidden concept layer which connects the visual feature and the word layer is discovered by fitting a generative model to the training image and annotation words through an Expectation-Maximization (EM) based iterative learning proced...
Ruofei Zhang, Zhongfei (Mark) Zhang, Mingjing Li,
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where MMS
Authors Ruofei Zhang, Zhongfei (Mark) Zhang, Mingjing Li, Wei-Ying Ma, HongJiang Zhang
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