Local Image Descriptor using VQ-SIFT for Image Retrieval

In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventional algorithm while the computational cost is significantly reduced.

Authors:

• Qiu Chen
• Feifei Lee
• Koji Kotani
• Tadahiro Ohmi

Keywords:

• SIFT feature
• Vector quantization histogram
• Localdescriptor
• Image retrieval.

References:

[1] C. Harris and M. Stephens, "A combined corner and edge detector," In
Alvey Vision Conference, 1988, pp. 147-151.
[2] D. G. Lowe, "Object recognition from local scale- invariant features," In
Proceedings of International Conference on Computer Vision, 1999,
pp.1150-1157.
[3] W. T. Freeman and E. H. Adelson, "The design and use of steerable
filters," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.13,
no.9, 1991, pp. 891-906.
[4] J. Koenderink and A. van Doorn, "Representation of local geometry in
the visual system," In Biological Cybernetics, vol.55, 1987, pp. 367-375.
[5] F. Schaffalitzky and A. Zisserman, "Multi-view matching for unordered
image sets," In Proceedings of European Conference on Computer
Vision, vol.1, 2002, pp. 414-431.
[6] L. Van Gool, T. Moons, and D. Ungureanu, "Affine/photometric
invariants for planar intensity patterns," In Proceedings of European
Conference on Computer Vision, 1996.
[7] D. G. Lowe, "Distinctive image features from scale-invariant
keypoints," International Journal of Computer Vision, vol.60, no.2,
2004, pp. 91-110.
[8] R. Fergus, P. Perona, and A. Zisserman, "Object class recognition by
unsupervised scale-invariant learning," In Proceedings of Computer
Vision and Pattern Recognition, Jun. 2003.
[9] K. Mikolajczyk and C. Schmid, "A performance evaluation of local
descriptors," In Proceedings of Computer Vision and Pattern
Recognition, Jun. 2003.
[10] K. Kotani, Q. Chen, and T. Ohmi, "Face recognition using vector
quantization histogram method," In Proceedings of 2002 International
Conference on Image Processing, vol. II of III:II-105-II-108, 2002.
[11] A.Gersho and R.M.Gray, Vector Quantization and Signal Compression,
Kluwer Academic, 1992.
[12] W. T. Freeman and M. Roth, "Orientation histograms for hand gesture
recognition," In Proceedings of International Workshop on Automatic
Face and Gesture Recognition, IEEE Computer Society, Zurich,
Switzerland, 1995, pp. 296-301.
[13] http://phd.serkangenc.com/orientation/orientation.php.
[14] AT&T Laboratories Cambridge, The Database of Faces, at
http://www.cl. cam.ac.uk/research/dtg/attarchive/facedatabase.html.
[15] http://www.cs.cmu.edu/˜yke/pcasift/.
[16] T. Deselaers, D. Keysers, and H. Ney, "Features for image retrieval - a
quantitative comparison", 26th DAGM Symposium, vol. 3175 of
Lecture Notes in ComputerScience , Germany, pp. 228-236, 2004.
[17] Q. Chen, K. Kotani, F. F. Lee, and T. Ohmi, "Robust VQ-based Local
Descriptor for SIFT Feature," Proceeding of the International
Conference on Image and Vision Computing (ICIVC 2009), pp.
1329-1333, France, Jun. 2009.
[18] H. Tamura, S. Mori, and T. Yamawaki, "Textural features corresponding
to visual perception", IEEE Transaction on Systems, Man, and
Cybernetics, vol. 8, no. 6, 460-472, 1978.