Magalhaes, Joao and Rüger, Stefan
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|DOI (Digital Object Identifier) Link:||http://doi.org/10.1145/1277741.1277923|
|Google Scholar:||Look up in Google Scholar|
In this paper we formulate image retrieval by text query as a vector space classification problem. This is achieved by creating a high-dimensional visual vocabulary that represents the image documents in great detail. We show how the representation of these image documents enables the application of well known text retrieval techniques such as Rocchio tf-idf and naíve Bayes to the semantic image retrieval problem. We tested these methods on a Corel images subset and achieve state-of-the-art retrieval performance using the proposed methods.
|Item Type:||Conference Item|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Users 8580 not found.|
|Date Deposited:||09 Oct 2008 13:02|
|Last Modified:||05 Oct 2016 12:52|
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