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Attribute-Graph: A Graph based approach to Image Ranking

Prabhu, Nikita and Babu, Venkatesh R (2015) Attribute-Graph: A Graph based approach to Image Ranking. In: IEEE International Conference on Computer Vision, DEC 11-18, 2015, Santiago, CHILE, pp. 1071-1079.

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Official URL: http://dx.doi.org/10.1109/ICCV.2015.128

Abstract

We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic similarity to a given query image. An Attribute-Graph is an undirected fully connected graph, incorporating both local and global image characteristics. The graph nodes characterise objects as well as the overall scene context using mid-level semantic attributes, while the edges capture the object topology. We demonstrate the effectiveness of Attribute-Graphs by applying them to the problem of image ranking. We benchmark the performance of our algorithm on the `rPascal' and `rImageNet' datasets, which we have created in order to evaluate the ranking performance on complex queries containing multiple objects. Our experimental evaluation shows that modelling images as Attribute-Graphs results in improved ranking performance over existing techniques.

Item Type: Conference Proceedings
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Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Information Sciences > Supercomputer Education & Research Centre
Date Deposited: 08 Oct 2016 05:19
Last Modified: 08 Oct 2016 05:19
URI: http://eprints.iisc.ernet.in/id/eprint/54679

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