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A Novel Approach Towards Large Scale Cross-Media Retrieval

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Abstract

With the rapid development of Internet and multimedia technology, cross-media retrieval is concerned to retrieve all the related media objects with multi-modality by submitting a query media object. Unfortunately, the complexity and the heterogeneity of multi-modality have posed the following two major challenges for cross-media retrieval: 1) how to construct a unified and compact model for media objects with multi-modality, 2) how to improve the performance of retrieval for large scale cross-media database. In this paper, we propose a novel method which is dedicate to solving these issues to achieve effective and accurate cross-media retrieval. Firstly, a multi-modality semantic relationship graph (MSRG) is constructed using the semantic correlation amongst the media objects with multi-modality. Secondly, all the media objects in MSRG are mapped onto an isomorphic semantic space. Further, an efficient indexing MK-tree based on heterogeneous data distribution is proposed to manage the media objects within the semantic space and improve the performance of cross-media retrieval. Extensive experiments on real large scale cross-media datasets indicate that our proposal dramatically improves the accuracy and efficiency of cross-media retrieval, outperforming the existing methods significantly.

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Bo Lu, Guo-Ren Wang (Member, CCF, ACM, IEEE) & Ye Yuan

Authors
  1. Bo Lu
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  2. Guo-Ren Wang
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  3. Ye Yuan
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Corresponding author

Correspondence to Bo Lu.

Additional information

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61025007, 60933001, 61100024, the National Basic Research 973 Program of China under Grant No. 2011CB302200-G, the National High Technology Research and Development 863 Program of China under Grant No. 2012AA011004, and the Fundamental Research Funds for the Central Universities of China under Grant No. N110404011.

*The preliminary version of the paper was published in the Proceedings of the 2012 Computational Visual media Conference.

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Lu, B., Wang, GR. & Yuan, Y. A Novel Approach Towards Large Scale Cross-Media Retrieval. J. Comput. Sci. Technol. 27, 1140–1149 (2012). https://doi.org/10.1007/s11390-012-1292-2

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  • DOI: https://doi.org/10.1007/s11390-012-1292-2

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