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Reseach Article

Multimodal Information Retrieval: Challenges and Future Trends

by Mohammad Ubaidullah Bokhari, Faraz Hasan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 14
Year of Publication: 2013
Authors: Mohammad Ubaidullah Bokhari, Faraz Hasan
10.5120/12951-9967

Mohammad Ubaidullah Bokhari, Faraz Hasan . Multimodal Information Retrieval: Challenges and Future Trends. International Journal of Computer Applications. 74, 14 ( July 2013), 9-12. DOI=10.5120/12951-9967

@article{ 10.5120/12951-9967,
author = { Mohammad Ubaidullah Bokhari, Faraz Hasan },
title = { Multimodal Information Retrieval: Challenges and Future Trends },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 14 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number14/12951-9967/ },
doi = { 10.5120/12951-9967 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:15.480158+05:30
%A Mohammad Ubaidullah Bokhari
%A Faraz Hasan
%T Multimodal Information Retrieval: Challenges and Future Trends
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 14
%P 9-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Multimodal information retrieval is a research problem of great interest in all domains, due to the huge collections of multimedia data available in different contexts like text, image, audio and video. Researchers are trying to incorporate multimodal information retrieval using machine learning, support vector machines, neural network and neuroscience etc. to provide an efficient retrieval system that fulfills user need. This paper is an overview of multimodal information retrieval, challenges in the progress of multimodal information retrieval.

References
  1. G. Hubert and J. Mothe, "An adaptable search engine for multimodal information retrieval". J. Am. Soc. Inf. Sci. , 60: 1625–1634. doi: 10. 1002/asi. 21091, 2009.
  2. E. H. Y. Lim et al. , "Knowledge Seeker - Ontology Modelling for Information Search and Management", Springer Berlin Heidelberg, Vol. 8, pp. 27-36, 2011.
  3. V. Lavrenko, and W. B. Croft, "Relevance Models in Information Retrieval", Language Modeling for Information Retrieval, W. Bruce Croft and John Lafferty, ed. , pp. 11-56, Kluwer Academic Publishers, Boston, 2003.
  4. R. S. Dubey, R. Choubey and J. Bhattacharjee, "Multi Feature Content Based Image Retrieval", (IJCSE) International Journal on Computer Science and Engineering, Vol. 02, No. 06, 2010, 2145-2149.
  5. E. Kasutani, "Image retrieval apparatus and image retrieving method", US Patent application 2007.
  6. Y. Chen and J. Z. Wang, "A Region-based fuzzy feature matching approach to content-based image retrieval", IEEE Trans. On PAMI, 24(9):1252-1267, 2002.
  7. G. Csurka et al. , "Visual categorization with bags of keypoints". In Proc. of the ECCV Workshop on Statistical Learning for Computer Vision 2004.
  8. F. Perronnin et al. , "Large-scale image retrieval with compressed ?sher vectors". In Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
  9. F. Alhwarin et al. , "Improved SIFT-Features Matching for Object Recognition"; BCS International Academic Conference 2008 – Visions of Computer Science, pp. 179-190; 2008.
  10. S. Sarin and W. Kameyama, "Joint Equal Contribution of Global and Local Features for Image Annotation", CLEF working notes, 2009.
  11. J. C. Haartsen et. al. , "Adaptive Display for Enhancing Audio Playback. ", U. S. Patent Application 12/209,300, filed September 12, 2008.
  12. A. Axenopoulos et al. , "I-SEARCH: A Unified Framework for Multimodal Search and Retrieval", in Proc. Future Internet Assembly, 2012, pp. 130-141.
  13. Urban, Jana, J. M. Jose, and C. J. V. Rijsbergen. "An adaptive technique for content-based image retrieval", Multimedia Tools and Applications 31 no. 1, 2006, 1-28.
  14. S-F. Chang, "Multimedia access and the state of the art and future directions", Proc. of ACM Multimedia, Nov. 1999, 443-445.
  15. A. Jaimes et al. , "Multimedia Information Retrieval: What is it, and why isn't anyone using it?" ACM MIR-05, Singapore 2005.
  16. M. Davis. S. King. N. Good, and R. Sarvas, "From context to content: leveraging context to infer media metadata", Proc. of ACM Multimedia. Oct. 2004, 188-195.
  17. W. Farag and H. Abdel-Wahab, "A human-based technique for measuring video data similarity", Proc. of the 8th IEEE International Symposium on Computers and Communications, Turkey, 2003, 769-774.
  18. A. Hauptmann and M. Christel, "Successful approaches in the TREC video retrieval evaluations", Proc. of ACM Multimedia, Oct. 2004, 668-675.
  19. N. Aggarwal, Dr. Nupur Prakash and Dr. Sanjeev Sofat, "Mining Techniques for Integrated Multimedia Repositories: A Review", BVICAM'S International Journal of Information Technology, Issue 1, January-July, 2009 Vol. 1 No. 1.
  20. R. A. Bolt, "Put that there: voice and gesture at the graphic interface", Computer Graphics 1980, Vol. 14, No. 3, pp. 262–270.
  21. M. M. Kokar, J. A. Tomasik, and J. Weyman, "Formalizing classes of information fusion systems", Information Fusion 2004, Vol. 5, No. 4, pp. 189–202.
  22. A. K. Jain, and A. Ross, "Multibiometric systems", Communications of the ACM, Special Issue on Multimodal Interfaces 2004, Vol. 47, No. 1, pp. 34–40.
  23. A. Ross, and A. K. Jain, "Multimodal biometrics: an overview", Proceedings of EUSIPCO, 2004, pp. 1221–1224.
  24. J. Kludas, E. Bruno, and S. M. Maillet, "Information fusion in multimedia information Retrieval", Proceedings of 5th International Workshop on Adaptive Multimedia Retrieval: Retrieval, User, and Semantics, Paris, France, 2007, pp. 147–159.
  25. Y. Wang and A. N. Venetsanopoulos, "Information Fusion for Multimodal Analysis and Recognition", Multimedia Image and Video Processing, Second Edition. Mar 2012, 153 -171.
  26. X. Zhou and T. Huang, "Relevance feedback in content-based image retrieval some recent Advances", Proc. Of the 6th Joint Conf. on Information Sciences. 2002. 15-18.
  27. R. Sarukkai, "Video search: opportunities and challenges", Proc. of the ACM workshop on Multimedia information Retrieval, 2005, 3-8.
Index Terms

Computer Science
Information Sciences

Keywords

Multi Modal Information Retrieval Information Retrieval Machine Learning SVM Semantic Gap Query Reformulation Fusion Techniques