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ImageTerrier: an extensible platform for scalable high-performance image retrieval

Published:05 June 2012Publication History

ABSTRACT

ImageTerrier is a novel easily extensible open-source, scalable, high-performance search engine platform for content-based image retrieval applications. The platform provides a comprehensive test-bed for experimenting with bag-of-visual-words image retrieval techniques. It incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures. ImageTerrier is written as an extension to the open-source Terrier, "Terabyte Retriever", test-bed platform for textual information retrieval research. The ImageTerrier platform is demonstrated to successfully index and search a corpus of over 10 million images containing just under 10,000,000,000 quantised SIFT visual terms.

References

  1. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  2. J. S. Hare, S. Samangooei, and D. P. Dupplaw. Open-IMAJ and ImageTerrier: Java libraries and tools for scalable multimedia analysis and indexing of images. In Proceedings of ACM Multimedia 2011, MM '11, pages 691--694. ACM, 2011. ISBN 978-1-4503-0616-4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. S. Heinz and J. Zobel. Efficient single-pass index construction for text databases. J. Am. Soc. Inf. Sci. Technol., 54:713--729, June 2003. ISSN 1532--2882. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. H. Jegou, M. Douze, and C. Schmid. Hamming embedding and weak geometric consistency for large scale image search. In Proceedings of ECCV 2008, ECCV '08, pages 304--317, Berlin, Heidelberg, 2008. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91--110, January 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. Lux and S. A. Chatzichristofis. Lire: lucene image retrieval: an extensible java cbir library. In Proceedings of ACM Multimedia 2008, MM '08, pages 1085--1088. ACM, 2008. ISBN 978-1-60558-303-7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. In P. L. Rosin and A. D. Marshall, editors, BMVC. British Machine Vision Association, 2002. ISBN 1-901725-19-7.Google ScholarGoogle ScholarCross RefCross Ref
  8. K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. V. Gool. A comparison of affine region detectors. IJCV, 65(1/2):43--72, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J.-M. Morel and G. Yu. ASIFT: A New Framework for Fully Affine Invariant Image Comparison. SIAM J. Img. Sci., 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. D. Nistér and H. Stewénius. Scalable recognition with a vocabulary tree. In CVPR, pages 2161--2168, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. I. Ounis, G. Amati, V. Plachouras, B. He, C. Macdonald, and C. Lioma. Terrier: A High Performance and Scalable Information Retrieval Platform. In Proc SIGIR, 2006.Google ScholarGoogle Scholar
  12. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In CVPR, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  13. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, pages 1470--1477, October 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D. M. Squire, W. Müller, H. Müller, and J. Raki. Content-based query of image databases, inspirations from text retrieval: Inverted files, frequency-based weights and relevance feedback. In PATTERN RECOGNITION LETTERS, pages 143--149, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. I. H. Witten, A. Moffat, and T. C. Bell. Managing Gigabytes: Compressing and Indexing Documents and Images. Morgan Kaufmann, San Francisco, CA, 2. edition, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      ICMR '12: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
      June 2012
      489 pages
      ISBN:9781450313292
      DOI:10.1145/2324796

      Copyright © 2012 ACM

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      New York, NY, United States

      Publication History

      • Published: 5 June 2012

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      ICMR '12 Paper Acceptance Rate50of145submissions,34%Overall Acceptance Rate254of830submissions,31%

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