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Autor
Skulimowski Andrzej M.J. (Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie), Rotter Paweł (Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie)
Tytuł
Applying Reference Sets in Content-based Interactive Image Retrieval
Źródło
Multiple Criteria Decision Making / University of Economics in Katowice, 2009, vol. 4, s. 185-202, bibliogr. 23 poz.
Słowa kluczowe
Podejmowanie decyzji, Multimedia, Bazy danych, Optymalizacja wielokryterialna
Decision making, Multimedia, Databases, Multiple criteria optimization
Uwagi
summ., Korespondencja z redakcją: numeracja wpisana za zgodą redakcji (wynika z ciągłości wydawniczej serii MCDM) - brak numeracji na stronie tytułowej
Abstrakt
The search for graphical objects in multimedia databases is a challenging field of current research and an emerging area of application of multicriteria decision theory. It is characterised by co-existence of qualitative, quantitative, and graphical criteria and gradual approximation of preference structures during the search. Here, we propose a new approach to image search based on preference information in form of reference images provided by the user interacting with an intelligent search system. Such information can be used in image retrieval systems with relevance feedback for complex graphical objects such as leisure facilities, human faces etc. Reference sets can be combined with any other method of content-based image retrieval (CBIR), resulting in a refined search. Computational experiments have proven that the proposed approach is computationally efficient. Finally, we provide a real-life illustration of the methods proposed: an image-based hotel selection procedure. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Szkoły Głównej Handlowej
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
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Bibliografia
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  2. Dubois D., Kaci S., Prade H.: CP-Nets and Possibilistic Logic: Two Approaches to Preference Modelling. Steps Towards a Comparison. In: Proceedings of the Multidisciplinary IJCAI-05 Workshop on Advances in Preference Handling. R. Brafman, U. Junker (eds). Edinburgh, Scotland, July 31 - August 1, 2005, pp. 79-84.
  3. Goodrum A.: Image Information Retrieval: An Overview of Current Research. "Informing Science" 2000. Special Issue of Information Science Research, Vol. 3, No. 2, pp. 63-66.
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  5. Ishikawa Y., Subramanya R., Faloutsos C.: MindReader: Querying Databases Through Multiple Examples. 24th VLDB Conference, New York 1998, pp. 218- -227.
  6. Lew M.S.: Principles of Visual Information Retrieval. Springer, London 2001.
  7. Mehrotra S., Chakrabarti K., Ortega M., Rui Y., Huang T.S.: Multimedia Analysis and Retrieval System. In: Proc. of The 3rd Int. Workshop on Information Retrieval Systems. Como, Italy September 25-27, 1997, pp. 39-45.
  8. Müller H., Müller W., Marchand-Maillet S., Squire D.McG.: Strategies for Positive and Negative Relevance Feedback in Image Retrieval. In: Proc. of the International Conference on Pattern Recognition (ICPR'2000), Vol. 1 of Computer Vision and Image Analysis, Barcelona, Spain, September 3-8, 2000, pp. 1043-1046.
  9. Müller H., Müller W., Squire D.McG., Marchand-Maillet S., Pun T.: Learning Features Weights from User Behaviour in Content-Based Image Retrieval. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. S.J. Simoff, O.R. Zaiane (eds). Workshop on Multimedia Data Mining MDM/KDD2000, Boston, MA, August 20-23 2000 pp. 67-72.
  10. Park J., Sandberg I.W.: Universal Approximation Using Radial-Basis-Function Networks. "Neural Computation" 1991, 3, pp. 246-257.
  11. Rocchio J.J.: Relevance Feedback in Information Retrieval. In: The SMART Retrieval System - Experiments in Automatic Document Processing. G. Salton (ed.). Prentice Hall, Englewood Cliffs, N.J. 1971. pp. 313-323.
  12. Rotter P. Application of Multicriteria Optimisation Methods in Image Interpretation (in Polish). PhD Thesis. Akademia Górniczo-Hutnicza, Kraków 2004.
  13. Rotter P., Skulimowski A.M.J.: A New Approach to the Interactive Visual Search with RBF Networks Based on Preference Modelling. In: Artificial Intelligence and Soft Computing - ICAIS 2008. Lecture Notes in Computer Science - Lecture Notes in Artificial Intelligence LNCS-LNAI). L. Rutkowski, R. Tadeusiewicz, L.A. Zadeh, J.M. Żurada (eds). Vol. 5097, Springer, Berlin 2008, pp. 861-873.
  14. Rotter P., Skulimowski A.M.J., Kotropoulos C., Pitas I.: Fast Shape Matching Using The Hausdorff Distance. Proceedings of Mirage 2005. INRIA Rocquencourt, France March, 1-2 2005, pp. 205-211.
  15. Rui Y., Huang T.S., Chang S.F.: Image Retrieval: Current Techniques, Promising Directions and Open Issues. "Journal of Visual Communication and Image Representation" March 1999, Vol. 10, pp. 39-62.
  16. Rui Y., Huang T.S., Mehrotra S.: Content-Based Image Retrieval with Relevance Feedback in MARS Proc. of IEEE Int. Conf. on Image Processing '97, Santa Barbara October 26-29, 1997, pp. 815-818.
  17. Rui Y., Huang T.S., Mehrotra S.: Relevance Feedback Techniques in Interactive Content-Based Image Retrieval. Proc. of IS&T and SPIE Storage and Retrieval of Image and Video Databases VI, San Jose, CA January 24-30, 1998, pp. 25-36.
  18. Servetto S., Rui Y., Ramchandran K., Huang T.S.: A Region-Based Representation of Images in MARS. "Journal on VLSI Signal Processing Systems" October 1998, Special Issue on Multimedia Signal Processing Guest Editors: Yao Wang & Amy Reibman, Vol. 20, Iss. 2, pp. 137-150.
  19. Skulimowski A.M.J.: Decision Support Systems Based on Reference Sets. AGH University Publishers, Kraków 1996, p. 167.
  20. Skulimowski A.M.J.: Methods of Multicriteria Decision Support Based on Reference Sets. In: Advances in Multiple Objective and Goal Programming. R. Caballero, F. Ruiz, R.E. Steuer (eds). Lecture Notes in Economics and Mathematical Systems, 455, Springer, Berlin-Heidelberg-New York 1997, pp. 282- 290.
  21. Skulimowski A.M.J., Rotter P.: Innovative Algorithms for Image Classification Based on the Hausdorff Distance. In: Transfer Technologii w Informatyce i Automatyce Technology Transfer in Computer Science and Automation). A.M.J. Skulimowski (ed.). Progress & Business Publishers, Kraków 2006, pp. 169-244.
  22. Smith J.R., Chang S.F.: VisualSEEk: A Fully Automated Content-Based Image Query System. In: Proc. ACM Intern. Conf. Multimedia. ACM Press, Boston, MA May 1996, pp. 87-98.
  23. Spink A., Losee R.: Feedback in Information Retrieval. "Annual Review of Information Science and Technology" 1996, Vol. 31, pp. 33-78
Cytowane przez
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ISSN
2084-1531
Język
eng
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