RELEVANCE FEEDBACK AS AN INTERACTIVE NAVIGATION TOOL

Daniele Borghesani, Costantino Grana, Rita Cucchiara

Abstract

Image collections are searched in common retrieval systems in many different ways, but the typical presentation is by means of a grid styled view. In this paper we try to suggest a novel use of relevance feedback as a tool to warp the view and allow the user to spatially navigate the image collection, and at the same time focus on his retrieval aim. This is obtained by the use of a distance based space warping on the 2D projection of the distance matrix.

References

  1. Andoni, A. and Indyk, P. (2006). Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In IEEE Symposium on Foundations of Computer Science, pages 459-468.
  2. Baraldi, S., Bimbo, A. D., Landucci, L., and Torpei, N. (2009). Natural interaction. In Encyclopedia of Database Systems, pages 1880-1885. Springer.
  3. Bay, H., Ess, A., Tuytelaars, T., and Van Gool, L. (2008). Speeded-Up Robust Features (SURF). Comput Vis Image Und, 110(3):346-359.
  4. Chang, Y., Kamataki, K., and Chen, T. (2009). Mean shift feature space warping for relevance feedback. In IEEE Image Proc, pages 1849-1852.
  5. Faloutsos, C. and Lin, K.-I. (1995). Fastmap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. In ACM SIGMOD International Conference on Management of Data, pages 163-174.
  6. Heesch, D. (2008). A survey of browsing models for content based image retrieval. Multimed Tools Appl, 40:261-284.
  7. Hinton, G. E. and Roweis, S. T. (2002). Stochastic neighbor embedding. In Neu Inf Pro Syst, pages 833-840.
  8. Jaimes, A. and Sebe, N. (2007). Multimodal humancomputer interaction: A survey. Comput Vis Image Und, 108(1-2):116-134.
  9. Jégou, H., Douze, M., and Schmid, C. (2011). Product quantization for nearest neighbor search. IEEE T Pattern Anal, 33(1):117-128.
  10. Liu, D., Hua, K., Vu, K., and Yu, N. (2009). Fast query point movement techniques for large cbir systems. IEEE Transactions on Knowledge and Data Engineering, 21(5):729-743.
  11. Lowe, D. G. (2004). Distinctive Image Features from ScaleInvariant Keypoints. Int J Comput Vision, 60(2):91- 110.
  12. Mikolajczyk, K. and Schmid, C. (2005). A performance evaluation of local descriptors. IEEE T Pattern Anal, 27(10):1615-1630.
  13. Nowak, S., Nagel, K., and Liebetrau, J. (2011). The clef 2011 photo annotation and concept-based retrieval tasks. In Petras, V., Forner, P., and Clough, P. D., editors, CLEF (Notebook Papers/Labs/Workshop).
  14. Oliva, A. and Torralba, A. (2006). Building the gist of a scene: The role of global image features in recognition. Visual Perception, Progress in Brain Research, 155.
  15. Rennison, E. (1994). Galaxy of news: an approach to visualizing and understanding expansive news landscapes. In ACM symposium on User interface software and technology, pages 3-12.
  16. Roweis, S. T. and Lawrence, K. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, pages 2323-2326.
  17. Sammon, J. W. (1969). A nonlinear mapping for data structure analysis. IEEE T Comput, 18(5):401-409.
  18. Tenenbaum, J. B., Silva, V., and Langford, J. C. (2000). A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290(5500):2319-2323.
  19. Tuzel, O., Porikli, F., and Meer, P. (2008). Pedestrian Detection via Classification on Riemannian Manifolds. IEEE T Pattern Anal, 30(10):1713-1727.
  20. Walter, J. A. (2004). H-mds: a new approach for interactive visualization with multidimensional scaling in the hyperbolic space. Inform Syst, 29(4):273-292.
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Paper Citation


in Harvard Style

Borghesani D., Grana C. and Cucchiara R. (2012). RELEVANCE FEEDBACK AS AN INTERACTIVE NAVIGATION TOOL . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 54-59. DOI: 10.5220/0003858700540059


in Bibtex Style

@conference{visapp12,
author={Daniele Borghesani and Costantino Grana and Rita Cucchiara},
title={RELEVANCE FEEDBACK AS AN INTERACTIVE NAVIGATION TOOL},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={54-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003858700540059},
isbn={978-989-8565-04-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - RELEVANCE FEEDBACK AS AN INTERACTIVE NAVIGATION TOOL
SN - 978-989-8565-04-4
AU - Borghesani D.
AU - Grana C.
AU - Cucchiara R.
PY - 2012
SP - 54
EP - 59
DO - 10.5220/0003858700540059