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EnContRA: a generic multimedia information retrieval meta-framework

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Abstract

Over the last years, multimedia collections have largely increased as new items are produced every day, such as pictures, audio/music or video. In Multimedia Information Retrieval, this exponential growth leads content-based approaches to gain advantage over other solutions, not only because they take advantage of the intrinsic information contained in the objects, but also because they automatically process and extract it, reducing the burden taken by developers. Several domain specific frameworks have been developed to efficiently retrieve multimedia items empowering the creation of new content-based applications. However, these frameworks are attached to a specific media type, are too complex to be used in a fast prototyping environment, and are not very flexible nor extensible. To solve these issues, we developed EnContRA, an architectural meta-framework that provides generic building blocks for creating domain specific frameworks. Our meta-framework aims at being ready to be used for fast prototyping, with support for rich and multimodal queries, allowing validation of new descriptors, indexing structures or searching algorithms, while creating domain specific frameworks. In this paper we present the meta-framework architecture and describe in detail its modules and features. To validate the meta-framework, we created an image retrieval framework and a demo application that combines image descriptors with textual information, showing how the hierarchical design of EnContRA could be applied to a searching system and to empower the creation of queries.

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Notes

  1. http://obsearch.net/

  2. http://muvis.cs.tut.fi/

  3. http://mufin.fi.muni.cz

  4. http://lsd.fi.muni.cz/trac/messif/

  5. http://www.mmretrieval.net

  6. http://www.semanticmetadata.net/lire/

  7. http://lucene.apache.org/

  8. http://mpeg.chiariglione.org/standards/mpeg-7/mpeg-7.htm

  9. http://dtai.cs.kuleuven.be/ACE/doc/

  10. Source and documentation can be found at http://encontra.github.io/

  11. http://www.hibernate.org/

  12. http://openjpa.apache.org/

  13. http://jdbm.sourceforge.net/

  14. http://en.wikipedia.org/wiki/Actor_model/

  15. http://akka.io/

  16. http://openjdk.java.net/projects/mlvm/

References

  1. Amato G, Bolettieri P, Gennaro C, Rabitti F (2013) Quick and easy implementation of approximate similarity search with lucene. In: Digital libraries and archives, communications in computer and information science, vol. 354. Springer, pp 163–171

  2. Amato G, Debole F (2005) A native xml database supporting approximate match search. In: Rauber A, Christodoulakis S, Tjoa A (eds) Research and advanced technology for digital libraries, lecture notes in computer science, vol. 3652. Springer, Berlin, pp 69–80

    Google Scholar 

  3. Bach JR, Fuller C, Gupta A, Hampapur A, Horowitz B, Humphrey R, Jain RC, Shu CF (1996) Virage image search engine: an open framework for image management. SPIE, pp 76–87

  4. Baeza-Yates RA, Ribeiro-Neto B (1999) Modern information retrieval. Addison-Wesley Longman Publishing Co., Inc., Boston

    Google Scholar 

  5. Batko M, Novak D, Zezula P (2007) Messif: metric similarity search implementation framework. In: DELOS07

  6. Comer D (1979) Ubiquitous b-tree. ACM Comput Surv 11(2):121–137

    Article  MATH  Google Scholar 

  7. Fonseca MJ, Jorge JA (2003) Indexing high-dimensional data for content-based retrieval in large databases. In: DASFAA

  8. Huang TS, Electrical MRNO, Engineering C (1996) Multimedia analysis and retrieval system (mars) project. In: Proceeding of 33rd annual clinic on library application of data processing - digital image access and retrieval

  9. Kiranyaz S, Gabbouj M (2006) Generic content-based audio indexing and retrieval framework. IEE Proc Vision Image and Signal Process 153(3):285–297

    Article  Google Scholar 

  10. Lux M (2009) Caliph & emir: Mpeg-7 photo annotation and retrieval. In: Proceedings of the 17th ACM international conference on multimedia, MM ’09. ACM, New York, pp 925–926

    Google Scholar 

  11. Lux M, Chatzichristofis SA (2008) Lire: lucene image retrieval: an extensible java cbir library. In: Proceedings of the 16th ACM international conference on multimedia, MM ’08. ACM, New York, pp 1085–1088

    Google Scholar 

  12. Mcennis D, Mckay C, Depalle P (2005) Jaudio : a feature extraction library. In: International conference on music information retrieval

  13. Mcennis D, Mckay C, Fujinaga I (2006) Jaudio: additions and improvements. In: Proceeding of the 7th international conference on music information retrieval (ISMIR), p 385

  14. Novak D, Batko M (2009) Metric index: an efficient and scalable solution for similarity search. In: Proceedings of the 2009 2nd international workshop on similarity search and applications, SISAP ’09. IEEE Computer Society, Washington, pp 65–73

    Book  Google Scholar 

  15. Novak D, Batko M, Zezula P (2009) Generic similarity search engine demonstrated by an image retrieval application. In: Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval, SIGIR ’09. ACM, New York, pp 840–840

    Book  Google Scholar 

  16. Rajaraman A, Ullman JD (2011) Cambridge University Press

  17. Tzanetakis G, Cook P (2000) Marsyas: a framework for audio analysis. Organized Sound 4

  18. Wimmers E, Haas L, Roth M, Braendli C (1999) Using fagin’s algorithm for merging ranked results in multimedia middleware. In: Proceedings. 1999 IFCIS international conference on cooperative information systems, 1999. CoopIS 99, pp 267-278

  19. Zagoris K, Arampatzis A, Chatzichristofis SA (2010) www.mmretrieval.net: a multimodal search engine. In: Proceedings of the third international conference on SImilarity search and APplications, SISAP ’10. ACM, New York, pp 117–118

    Book  Google Scholar 

Download references

Acknowledgments

This work was supported by national funds through FCT –Fundação para a Ciência e a Tecnologia, under project PEst-OE/EEI/LA0021/2013, by ADI through the ColaDI project and through the Crush project, PTDC/EIA-EIA/108077/2008. Ricardo Dias was supported by FCT, grant reference SFRH/BD/70939/2010.

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Correspondence to Ricardo Dias.

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Dias, R., Fonseca, M.J., Silva, N. et al. EnContRA: a generic multimedia information retrieval meta-framework. Multimed Tools Appl 74, 3691–3713 (2015). https://doi.org/10.1007/s11042-013-1794-0

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