A Novel Bag-of-Object Retrieval Model To Predict Image Relevance
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Research Paper | Computer Science & Engineering | India | Volume 5 Issue 6, June 2016

A Novel Bag-of-Object Retrieval Model To Predict Image Relevance

Gouri K. Ghadge, G. J. Chhajed

Text based image search is now a days a routine work for which generally, image search re-ranking and image result summarization these two effective approaches are used. But these approaches are not suitable for the object queries. In this system, a novel bag-of-object retrieval model is designed to predict image relevance, which is specifically effective for object queries. In this approach, first, an object vocabulary is constructed which contains query-relative objects based on expanded query sets which considers the frequent object patches in the result image collection. Then training model is constructed on the basis of frequent object patches. The efficiency of the proposed model is demonstrated by comparing the results with image search re-ranking and image search result summarization.

Keywords: Re-ranking, summarization, object retrieval

Edition: Volume 5 Issue 6, June 2016

Pages: 1721 - 1725

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How to Cite this Article?

Gouri K. Ghadge, G. J. Chhajed, "A Novel Bag-of-Object Retrieval Model To Predict Image Relevance", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=NOV164602, Volume 5 Issue 6, June 2016, 1721 - 1725

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