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Generic Multimedia Database Architecture Based upon Semantic Libraries

Published: 01 December 2007 Publication History

Abstract

Semantic-based storage and retrieval of multimedia data requires accurate annotation of the data. Annotation can be done either manually or automatically. The retrieval performance of the manual annotation based approaches is quite good, as compared to approaches based on automatic annotation. However, manual annotation is time consuming and labor extensive. Therefore, it is quite difficult to apply this technique on huge volume of multimedia data. On the other hand, automatic annotation is commonly used to annotate the multimedia data based on low level features, which obviously lacks the semantic nature of the multimedia data. Yet, we have not come across with any such system which automatically annotate the multimedia data based on the extracted semantics accurately. In this paper, we have performed automatic annotation of the images by extracting their semantics (high level features) with the help of semantic libraries. Semantic libraries use semantic graphs. Each graph consists of related concepts along with their relationships. We have also demonstrated with the help of a case study that our proposed approach ensures an improvement in the semantic based retrieval of multimedia data.

References

[1]
Aghbari, A., and A. Makinouchi (2003). Semantic approach to image database classification and retrieval. NII Journal, 7.
[2]
Ardizzoni, S., I. Bartolini and M. Patella (1999). WindSurf: Region-based image retrieval using wavlets. In Proceedings of 10th International Workshop on Database and Extert Systems Applications.
[3]
Bartolini, I., P. Ciaccia and F. Waas (2001). FeedbackBypass: A New Approach to Interactive Similarity Query Processing. Technical Report CSITE-09-01, CSITE-CNR, 2001. Available at URL http://www-db.deis.unibo.it/MMDBGroup/TRs.html.
[4]
Bartolini, I., P. Ciaccia and F. Waas (2001). FeedbackBypass: A new approach to interactive similarity query processing. In Proceedings of the 27th International Conference on Very Large Data Bases (VLDB'01). Rome, Italy. pp. 201-210.
[5]
Böszörményi, L., C. Stary, H. Kosch and C. Becker (2001). Quality of service in distributed object systems and distributed multimedia object/component systems. In Proceedings of the Workshops on Object-Oriented Technology, vol. 2323. pp. 7-29.
[6]
Carson, C., S. Belongie, H. Greenspan and J. Malik (2002). Blobworld: image segmentation using expectation-maximization and its application to image querying. IEEE Trans. Pattern Anal, Machine Intel., 24(8), 1026- 1038.
[7]
Chamberlin, D., D. Florescu, J. Robie, J. Simeon and M. Stefanescu (2001). XQuery: A Query Language for XML. W3C Working Draft, Technical report.
[8]
Chang, E., K. Goh, G. Sychay and G. Wu (2003). CBSA: content-based soft annotation for multimodel image retrieval using Bayes point machine. CirSys Video, 13(1), 26-31.
[9]
Chen, Y., and J.Z. Wang (2002). A region-based fuzzy-matching approach to content-based image retrieval system. IEEE Trans. On Pattern Recognition Analysis and Machine Intelligence, 24(9).
[10]
Chen, Y., J.Z. Wang and R. Krovertz (2003). Content-based image retrieval by clustering. MIR'03.
[11]
Clark, J., and S. DeRose (1999). XML Path Language (XPath). Version 1.0. W3C Recommendation, Technical report.
[12]
Cohen, S., J. Mamou, Y. Kanza and Y. Sagiv (2003). XSEarch: a semantic search engine for XML. VLDB'03.
[13]
Corcho, O., and A.G. Pérez (2000). A roadmap to ontology specification languages. In Proceedings of Knowledge Engineering and Knowledge Management. Methods, Models, and Tools: 12th International Conference, EKAW 2000, vol. 1937. Juan-les-Pins, France.
[14]
Cox, I.J., M.L. Millar, T.P. Minka, T.V. Papathomas and P.N. Yianilos (2000). The Bayesian image retrieval system, pichunter: theory, implementation, and psychophysical experiments. IEEE Trans. Image Processing, 9(1), 20-37.
[15]
Cusano, C., G. Ciocca and R. Schettini (2004). Image annotation using SVM. In Proceedings of Internet Imaging IV, vol. SPIE 5304.
[16]
Dasiopoulou, S., V.K. Papastathis, V. Mezaris, I. Kompatsiaris and M.G. Strintzis (2004). An ontology framework for knowledge-assisted semantic video analysis and annotation. In Proc. 4th International Workshop on Knowledge Markup and Semantic Annotation (SemAnnot 2004) at the 3rd International Semantic Web Conference (ISWC 2004).
[17]
De Vries, A.P. (1998). Mirror: multimedia query processing in extensible databases. In 14th Twente Workshop on Language Technology. Language Technology in Multimedia Information Retrieval, Enschede, The Netherlands.
[18]
Delon, J., A. Desolneux, J. Lisani and A. Petro (2005). Histogram Analysis and Segmentation by a Contrario Methods. Univ. Illes Balears, Spain.
[19]
Deutsch, A., M. Fernandez, D. Florescu, A.Y. Levy and D. Suciu (1998). XMLQL: A Query Language for XML. W3C, Technical report.
[20]
Dimitrova, N., and F. Golshani (1994). Rx for semantic video database retrieval. In Proceedings of ACM Multimedia' 94. San Francisco. pp. 219-226.
[21]
Döller, M., and H. Kosch (2003). An MPEG-7 multimedia cartridge. In Proc. Of the SPIE Conference on Multimedia Computing and Networking 2003 (MMCN 2003). Santa Clara, California, USA. pp. 126-137.
[22]
Dorai, C., A. Mauthe, F. Nack, L. Rutledge, T. Sikora and H. Zettl (2002). Media semantics: who needs it and why? In Multimedia'02, December 1-6, Juan-les-Pins, France.
[23]
Dunckley, L. (2003). Multimedia databases - an object-relational approach. ISBN # 0 201 78899 3, pub 2003, Chapter 5, page 117-122.
[24]
Duygulu, P.K., N. Barnard, D. Freitas and D.A. Forsyth (2002). Object recognition as machine translation: learning a lexicon for a fixed image image vocabular. In Proceedings of 7th European Conference on Computer Vision.
[25]
Faloutsos, C., R. Barber, M. Flickner, J. Hafner, W. Niblack, D. Petkovic and W. Equitz (1994). Efficient and effective querying by image content. J. Intell. Inform. Syst., 3(3-4), 231-262.
[26]
Giunchiglia, F., P. Shvaiko and M. Yatskevich (2003). Semantic matching. in The Knowledge Engineering Review.
[27]
Gómez-Pérez, A. (2001). Evaluation of ontologies. International Journal of Intelligent Systems, 16(3).
[28]
Gomez-Perez, A., and O. Corcho (2002). Ontology languages for the semantic web. In IEEE Intelligent Systems & Their Applications.
[29]
Gottlob, G., C. Koch and R. Pichler (2003). The complexity of XPath query evaluation. In PODS 2003, San Diego, CA.
[30]
Groppe, S., and S. Böttcher (2003). XPath query transformation based on XSLT stylesheets. In WIDM'03, New Orleans, Louisiana, USA.
[31]
Gruber, T.R. (1993). Toward principles for the design of ontologies used for knowledge sharing. Knowledge Systems Laboratory, Stanford University, Technical Report KSL-93-4. Communications of the ACM, 37(7), 48-53147.
[32]
Guo, G., A.K. Jain, W. Ma and H. Zhang (2002). Learning similarity measure for natural image retrieval with relevance feedback. IEEE Trans. On Neural Networks, 13(4), 811-820.
[33]
Hammiche, S., S. Benbernou, M. Hacid and A. Vakali (2004). Semantic retrieval of multimedia data. In MMDB'04, November 13, Washington, DC, USA.
[34]
Heesch, D., A. Vanlinsky and S. Ruger (2003). Performance comparison of different similarity models for CBIR with relevance feedback. Image and Video Retrieval Second International Conference, CIVR 2003. Urbana-Champaign, IL, USA, July 24-25. pp. 456-466.
[35]
Huang, T., S. Mehrotra and K. Ramchandran (1996). Multimedia analysis and retrieval system. In Proc. of 33rd Annual Clinic on Library Application of Data Processing Digital Image Access and Retrieval.
[36]
Iftikhar, N., Z. Zafar and S. Ali (2005). Context-aware querying in multimedia databases - a futuristic approach. In Proceedings of The 3rd World Enformatika Conference (WEC' 05), vol. 5. April 27-29, Istanbul, Turkey. pp. 140-143.
[37]
Iqbal, Q., and J.K. Aggarwal (2003). Feature integration, multi-image queries and relevance feedback in image retrieval. In 6th International Conference on Visual Information System (Visual 2003). Miami, Florida, Sep 24-26. pp. 467-474.
[38]
Jeon, J., V. Lavrenko and R. Manmatha (2003). Automatic image annotationand retrieval using cross-media relevance models. In Proceedings of 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.
[39]
Jiang, Y., and Z. Zhou (2004). SOM ensemble-based image segmentation. Neural Processing Letters, 20(3), 171-178.
[40]
Jiang, Y., K.-J. Chen and Z.-H. Zhou (2003). SOM based image segmentation. In: G. Wang, Q. Liu, Y. Yao and A. Skowron (Eds.), Lecture Notes in Artificial Intelligence, vol. 2639. Springer, Berlin. pp. 640-643.
[41]
Kang, F., R. Jin and J.Y. Chai (2004). Regularizing translation models for better automatic image annotation. CIKM'04.
[42]
Kosch, H., and M. Dollar (2005). Multimedia Database Systems: Where Are We Now? IASTED DBA Konferenz, Innsbruck, Österreich. Available at: www.itec.uni-klu.ac.at/~harald/MMDBoverview.pdf.
[43]
Kosch, H., L. Böszörményi, A. Bachlechner, B. Dörflinger, C. Hanin, C. Hofbauer, M. Lang, C. Riedler and R. Tusch (2001). SMOOTH - A distributed multimedia database system. In VLDB'2001. Rome, Italy. pp. 713-714.
[44]
Kosch, H., L. Böszörményi, R. Tusch, A. Bachlechner, B. Dörflinger, C. Hofbauer and C. Riedler (2000). The SMOOTH video db - demonstration of an integrated generic indexing approach. In Proceedings of the 8th ACM Multimedia Conference. Los Angeles, USA. ACM Press. pp. 495-496.
[45]
Kosch, H., L. Boszormenyi, M. Doller, M. Libsie, P. Schojer and A. Kofler (2005). The life cycle of multimedia metadata. IEEE MultiMedia, 12(1), 80-86.
[46]
Kuhn, W. (2003). Semantic reference systems. International Journal of Geographical Information Science.
[47]
Lavrenko, V., R. Manmatha and J. Jeon (2003). A model for learning the semantics of pictures. In Proceedings of Advance in Neutral Information Processing.
[48]
Li, J., and J.Z. Wang (2003). Automatic linguistic indexing of pictures by a statistical model approach. IEEE Trans. On Pattern Analysis and Machine Intelligence, 25(19), 1075-1088.
[49]
Li, J., and J.Z. Wang (2004). Studying digital imagery of ancient paintings by mixtures of stochastic models. IEEE Xplore, 13(3), 340-353.
[50]
Liu, Y., D. Zhang, G. Lu and W. Ma (2005). Region-based image retrieval with high-level semantic color names. In 11th International Multimedia Modeling Conference (MMM05). pp. 180-187.
[51]
Loncaric, S. (1998). A survey of shape analysis techniques. Pattern Recognition, 31(8), 983-1001.
[52]
Lux, M., and J. Becker (2002). XML and MPEG-7 for interactive annotation and retrieval using semantic metadata. Journal of Universal Computer Science (JUCS), Hg., 965-984.
[53]
McKenzie, M. (1996). Virage Versus the BLOB - Visual Information Retrieval Technology Drives a Search Engine. The Seybold Report on Internet Publishing.
[54]
Maedche, A., and S. Staab (2001). Ontology learning for the semantic web. IEEE Intelligent Systems.
[55]
Mehrotra, S., Y. Rui, M. Ortega-Binderberger and T.S. Huang (1997). Supporting content-based queries over Images in MARS. In Proc. IEEE Int'l Conf. On Multimedia Computing and System. pp. 632-633.
[56]
Mohan, A., C. Papageorgiou and T. Poggio (2001). Example-based object detection in images by components. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(4), 349-361.
[57]
Morgenstern, C., and B. Heisele (2003). Componenet-based recognition of objects in an office environment. In AI Memo 2003-024.
[58]
Nicola, N., and J. John (2003). XML parsing: A threat to database performance. In CIKM'03, Louisiana, USA.
[59]
Olivia, F.C., B. Taylor, A. Noakes, S. Markel, D. Torres and K.M. Drabenstott (2000). Browse and search patterns in a digital image database. Journal Information Retrieval, 4, 287-313.
[60]
Pal, N.R., and S. Pal (1993). A review on image segmentation techniques. Pattern Recognition, 26, 1277-1294.
[61]
Palus, H., and M. Bogdanski (2003). Clustering techniques in colour image segmentation. In Proceedings of the 4th Symposium on Methods of Artificial Intelligence. Gliwice, Poland. pp. 223-226.
[62]
Rehman, M.U., I. Ihsan, M.U. Ahmed, N. Iftikhar and A. Qadir (2005). Generic multimedia database architecture. In Proceedings of The 3rd World Enformatika Conference (WEC' 05), vol. 5. April 27-29, Istanbul, Turkey. pp. 128-131.
[63]
Robie, J., J. Lapp and D. Schach (1998). XML Query Language (XQL). Available at http://www.w3.org/TandS/QL/QL98/pp/xql.html.
[64]
Rode, H., and D. Hiemstra (2005). Conceptual language models for context-aware text retrieval. In Proceedings of the 13th Text Retrieval Conference (TREC). NIST Special Publications.
[65]
Rui, Y., T.S. Huang, M. Ortega and S. Mehrotra (1998). Relevance feedback: a power tool for interactive content-based retrieval. IEEE Trans. Circuits and video Technology, 8(5), 644-655.
[66]
Sheikholeslami, G., W. Change and A. Zhang (2002). SemQuery: Semantic clustering and quering on hetrogenous features for visual data. IEEE Trans. Knowledge and Data Engineering, 14(5), 988-1002.
[67]
Smith, J.R., and S.F. Chang (1997). Visually searching the web for content. IEEE Multimedia, 4(3), 12-20.
[68]
Sonka, M., Hlavac and R.V. Boyle (1998). Image Processing, Analysis, and Machine Vision, 2nd Ed. PWS, Pacific Grove, CA.
[69]
Su, X., and L. llebrekke (2002). A comparative study of ontology languages and tools. In Proceedings of Advanced Information Systems Engineering: 14th International Conference, CAiSE, Toronto, Canada.
[70]
Sumengen, B. (2004). Variational Image Segmentation and Curve Evolution on Natural Images. Publication#199, Vision Research Lab, Ph.D. Thesis, University of California, Santa Barbara.
[71]
Tork Roth, M., M. Arya, L. Haas, M. Carey, W. Cody, R. Fagin, P. Schwarz, J. Thomas and E. Wimmers (1996). The Garlic Project. In Proceeding of 1996 ACM SIGMOD International Conference on Management of Data. pp. 557.
[72]
Torralba, A. (2003). Contextual priming for object detection. International Journal of Computer Vision, 53(2), 169-191.
[73]
Torralba, A., and P. Sinha (2001). Statistical context priming for object detection. In International Conference on Computer Vision (ICCV'01), vol. 1. pp. 763-771.
[74]
Vailaya, A., M.A.T. Figueredo, A.K. Jain and H.-J. Zhang (2001). Image classification for content-based Indexing. IEEE Trans. Image Processing, 10(1), 117-130.
[75]
Wang, F., Y. Ma, H. Zhang and J.T. li (2005). A generic framework for semantic sports video analysis using dynamic Bayesian networks. In 11th International Multimedia Modelling Conference (MMM'05). pp. 115- 122.
[76]
Wang, J.Z., J. Li and G. Wiederhold (2001). SIMPLIcity: Semanitcs-sensitive integrated matching for picture libraries. IEEE Trans. Pattern Anal. Machine Intell., 23(9), 947-963.
[77]
Wiesman, F., S. Bocconi and B. Arsenijevic (2003). Intelligent information retrieval and presentation with multimedia databases. In DIR 2003, 4th Dutch-Belgian Information Retrieval Workshop.
[78]
Zhang, C., J. Naughton, D. DeWitt, Q. Luo and G. Lohman (2001). On supporting containment queries in relational database management systems. In Proceedings of the ACM SIGMOD International Conference on the Management of Data.

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cover image Informatica
Informatica  Volume 18, Issue 4
December 2007
146 pages

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IOS Press

Netherlands

Publication History

Published: 01 December 2007

Author Tags

  1. automatic annotation
  2. content-based image retrieval
  3. image abstract extraction
  4. multimedia database architecture
  5. semantic libraries

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