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. In this paper, we propose a novel method which is dedicate to achieve effective and accurate cross-media retrieval. Firstly, a Multi-modality Semantic Relationship Graph (MSRG) is constructed by 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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lew, M., Sebe, N., Djeraba, C., Jain, R.: Content-based multimeida information retrieval: State-of-the-art and challenges. ACM Trans. Multimeida Comput., Commun., Applic. 2(1), 1–19 (2006)
Smeaton, A.F., Over, P., Kraaij, W.: Evaluation campaigns and TRECVid. In: Proc. of MIR (2006)
Paramita, M., Sanderson, M., Clough, P.: Diversity in photo retrieval: overview of the Image CLEF photo task 2009. CLEF Working Notes (2009)
Naphade, M., Smith, J.R., Tesic, J., Chang, S.-F., Hsu, W., Kennedy, L., Hauptmann, A., Curtis, J.: Large-Scale Concept Ontology for Multimedia. IEEE Multimedia Magazine 13(3) (2006)
Hotelling, H.: Relations between two sets of variates. Biometrike 28, 321–377 (1936)
Zhang, H., Zhuang, Y., Wu, F.: Cross-modal correlation learning for clustering on image-audio dataset. In: ACM Multimeida (2007)
Yang, Y., Zhuang, Y., Wu, F.: Harmonizing hierarchical manifolds for multimedia document semantics understanding and cross-media retrieval. IEEE Transactions on Multimedia 10, 437–446 (2008)
Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: Proc of the VLDB Conference, pp. 426–435 (1997)
Christian, B.: A cost model for query processing in high dimensional data spaces. ACM Transactions on Database Systems 25, 129–178 (2000)
Zhuang, Y., Li, Q., Chen, L.: A Unified Indexing Structure for Efficient Cross-Media Retrieval. In: Zhou, X., Yokota, H., Deng, K., Liu, Q. (eds.) DASFAA 2009. LNCS, vol. 5463, pp. 677–692. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lu, B., Wang, G., Yuan, Y. (2012). Towards Large Scale Cross-Media Retrieval via Modeling Heterogeneous Information and Exploring an Efficient Indexing Scheme. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-34263-9_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34262-2
Online ISBN: 978-3-642-34263-9
eBook Packages: Computer ScienceComputer Science (R0)