On stability of adaptive similarity measures for content-based image retrieval

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7131 LNCS, Issue , 2012, Pages 346-357

  Beecks, Christian ^a   Seidl, Thomas ^a  

^a RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

adaptive similarity measure; average precision stability; content based image retrieval; evaluation measure; feature signature

Indexed keywords

CONTENT BASED IMAGE RETRIEVAL; EVALUATION MEASURES; FEATURE SIGNATURE; IMAGE DATABASE; IMAGE MODELS; MULTIMEDIA DATABASE; QUALITY CHANGE; RETRIEVAL PERFORMANCE; SIMILAR IMAGE; SIMILARITY MEASURE; USER-DEPENDENT;

CONTENT BASED RETRIEVAL; INFORMATION RETRIEVAL; QUALITY CONTROL; STABILITY;

SEARCH ENGINES;

EID: 84855769342     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-27355-1_33     Document Type: Conference Paper

References (26)

1. Beecks, C., Uysal, M.S., Seidl, T.: Signature quadratic form distances for content-based similarity. In: Proc. ACM International Conference on Multimedia, pp. 697-700 (2009)
2. Beecks, C., Uysal, M.S., Seidl, T.: A comparative study of similarity measures for content-based multimedia retrieval. In: Proc. IEEE International Conference on Multimedia & Expo, pp. 1552-1557 (2010)
3. Beecks, C., Uysal, M.S., Seidl, T.: Signature quadratic form distance. In: Proc. ACM International Conference on Image and Video Retrieval, pp. 438-445 (2010)
4. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys 40(2), 1-60 (2008)
5. Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples an incremental bayesian approach tested on 101 object categories. In: Proc. of the Workshop on Generative-Model Based Vision (2004)
6. Geusebroek, J.-M., Burghouts, G.J., Smeulders, A.W.M.: The Amsterdam Library of Object Images. International Journal of Computer Vision 61(1), 103-112 (2005)
7. Hu, R., Rüger, S., Song, D., Liu, H., Huang, Z.: Dissimilarity measures for content-based image retrieval. In: Proc. IEEE International Conference on Multimedia &Expo, pp. 1365-1368 (2008)
8. Huiskes, M.J., Lew, M.S.: The mir flickr retrieval evaluation. In: Proc. of the 1st ACM International Conference on Multimedia Information Retrieval, pp. 39-43 (2008)
9. Huttenlocher, D.P., Klanderman, G.A., Rucklidge, W.A.: Comparing Images Using the Hausdorff Distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 850-863 (1993)
10. Järvelin, K., Kekäläinen, J.: Cumulated gain-based evaluation of ir techniques. ACM Trans. Inf. Syst. 20, 422-446 (2002)
11. Kent, A., Berry, M.M., Luehrs, F.U., Perry, J.W.: Machine literature searching viii. operational criteria for designing information retrieval systems. American Documentation 6(2), 93-101 (1955)
12. Leow, W.K., Li, R.: The analysis and applications of adaptive-binning color histograms. Computer Vision and Image Understanding 94(1-3), 67-91 (2004)
13. Lew, M.S., Sebe, N., Djeraba, C., Jain, R.: Content-based multimedia information retrieval: State of the art and challenges. ACM Transactions on Multimedia Computing, Communications, and Applications 2(1), 1-19 (2006)
14. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91-110 (2004)
15. Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)
16. Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(10), 1615-1630 (2005)
17. Nene, S., Nayar, S.K., Murase, H.: Columbia Object Image Library (COIL-100). Technical report, Department of Computer Science, Columbia University (1996)
18. Park, B.G., Lee, K.M., Lee, S.U.: Color-based image retrieval using perceptually modified Hausdorff distance. Journal on Image and Video Processing 2008, 1-10 (2008)
19. Rubner, Y., Puzicha, J., Tomasi, C., Buhmann, J.M.: Empirical evaluation of dissimilarity measures for color and texture. Computer Vision and Image Understanding 84(1), 25-43 (2001)
20. Rubner, Y., Tomasi, C., Guibas, L.J.: The Earth Mover's Distance as a Metric for Image Retrieval. International Journal of Computer Vision 40(2), 99-121 (2000)
21. Sebe, N., Lew, M.S., Zhou, X., Huang, T.S., Bakker, E.M.: The state of the art in image and video retrieval. In: Proc. ACM International Conference on Image and Video Retrieval, pp. 1-8 (2003)
22. Sivic, J., Zisserman, A.: Video google: A text retrieval approach to object matching in videos. In: IEEE International Conference on Computer Vision, pp. 1470-1477 (2003)
23. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12), 1349-1380 (2000)
24. Tuytelaars, T., Mikolajczyk, K.: Local invariant feature detectors: a survey. Foundations and Trends in Computer Graphics and Vision 3(3), 177-280 (2008)
25. van Rijsbergen, C.J.: Information Retrieval. Butterworth (1979)
26. Wang, J.Z., Li, J., Wiederhold, G.: Simplicity: Semantics-sensitive integrated matching for picture libraries. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(9), 947-963 (2001)