Multimedia Tools and Applications

, Volume 77, Issue 3, pp 3009–3027 | Cite as

Joint graph regularization based modality-dependent cross-media retrieval

Article
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Abstract

Cross-media retrieval returns heterogeneous multimedia data of the same semantics for a query object, and the key problem for cross-media retrieval is how to deal with the correlations of heterogeneous multimedia data. Many works focus on mapping different modal data into an isomorphic space, so the similarities between different modal data can be measured. Inspired by this idea, we propose a joint graph regularization based modality-dependent cross-media retrieval approach (JGRMDCR), which takes into account the one-to-one correspondence between different modal data pairs, the inter-modality similarities and the intra-modality similarities. Meanwhile, according to the modality of the query object, this method learns different projection matrices for different retrieval tasks. Experimental results on benchmark datasets show that the proposed approach outperforms the other state-of-the-art algorithms.

Keywords

Cross-media retrieval Correlation analysis Joint graph regularization 

Notes

Acknowledgement

The work is partially supported by the National Natural Science Foundation of China (Nos. 61373081, 61572298, 61402268, 61401260, 61601268), the Key Research and Development Foundation of Shandong Province (No. 2016GGX101009) and the Natural Science Foundation of Shandong China (No.BS2014DX006, ZR2014FM012). We also gratefully acknowledge the support of NVIDIA Corporation with the donation of the TITAN X GPU used for this research.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Jihong Yan
    • 1
  • Huaxiang Zhang
    • 1
    • 2
  • Jiande Sun
    • 1
    • 2
  • Qiang Wang
    • 1
    • 2
  • Peilian Guo
    • 1
    • 2
  • Lili Meng
    • 1
    • 2
  • Wenbo Wan
    • 1
    • 2
  • Xiao Dong
    • 1
  1. 1.School of Information Science and EngineeringShandong Normal UniversityJinanChina
  2. 2.Institute of Data Science and TechnologyShandong Normal UniversityJinanChina

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