Recognition with local features: The kernel recipe

Proceedings of the IEEE International Conference on Computer Vision

Volumn 1, Issue , 2003, Pages 257-264

  Wallraven, Christian ^a   Caputo, Barbara ^b   Graf, Arnulf ^a  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

^b ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DATABASE SYSTEMS; LEARNING ALGORITHMS; NEURAL NETWORKS; OBJECT RECOGNITION; PATTERN MATCHING;

FEATURE MATCHING; LARGE SCALE RECOGNITION; SUPPORT VECTOR MACHINE;

FEATURE EXTRACTION;

EID: 0345414121     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iccv.2003.1238351     Document Type: Conference Paper

References (26)

1. A. Barla, F. Odone, A. Verri, "Image kernels", Proc. of ICPR workshop on SVM, 2002.
2. S. Belongie, J. Malik, J. Puchiza, "Matching Shapes", Proc. ICCV'01, 2001.
3. H. Bishof, H. Wildenauer, A. Leonardis, "Illumination insensitive eigenspaces", Proc. of ICCV'01, 2001.
4. V. Blanz, T. Vetter, "A Morphable Model for the Synthesis of 3D Faces", Proc. of SIGGRAPH'99, 1999.
5. C. Burges, "Geometry and Invariance in Kernel based Methods", Advances in Kernel Methods, MIT press, 1998.
6. B. Caputo, S. Bouattour, H. Niemann, "Robust appearance-based object recognition using a fully connected Markov random field", Proc. of ICPR'02, 2002.
7. B. Caputo, G. Dorko. "How to combine color and shape information for 3D object recognition: kernels do the trick". Advances in Neural Information Processing Systems, Vol 15, 2003.
8. O. Chapelle, P. Haffner, and V. Vapnik, SVMs for histogram-based image classification. IEEE Trans. on Neural Networks, 10(5), 1999.
9. N. Cristiani, J. S. Taylor, "An introduction to support vector machines and other kernel-based learning methods", Cambridge UP, 2000.
10. R. O. Duda, P. E. Hart, D. G. Stork, Pattern Classification, Wiley and sons, 2001.
11. T. Joachims, SVMligh available at http://www.cs.cornell.edu/People/tj/svm_light
12. I. Laptev, T. Lindeberg, "Interest point detection and scale selection in space-time", to appear in Proc. of Scale-Space'03, Springer, LNCS, 2003.
13. B. Leibe, B. Schiele, "Analyzing appearance and contour based methods for object categorization", CVPR'03, 2003.
14. S. Z. Li, Q. Fu, L. Gu, B. Schölkopf, Y. Cheng, H. Zhang, "Kernel machine based learning for multi-view face detection and pose estimation", Proc. ICCV'01, 2001.
15. D. Lowe, "Object recognition from local scale invariant features", Proc. ICCV'99, 1999.
16. K. Mikolajczyk, C. Schmid, "An affine invariant interest point detector", Proc. ECCV'02, 2002.
17. S. A. Nene, S. K. Nayar and H. Murase, "Columbia Object Image Library (COIL-100)," TR CUCS-006-96, 1996.
18. M. Pontil, A. Verri, "Support vector machines for 3D object recognition", IEEE TPAMI, 20(6), 637-646, 1998.
19. D. Roobaert, M. Zillich, J. O. Eklundh, "A pure learning approach to background invariant object recognition using pedagogical support vector learning", Proc. CVPR'01, 2001.
20. F. Schaffailitzky, A. Zissermann "Viewpoint invariant texture matching and wide baseline stereo", Proc. ICCV'01, 2001.
21. B. Schiele, J. L. Crowley, "Recognition without correspondence using multidimensional receptive field histograms", IJCV, 36(1), 31-50, 2000.
22. C. Schmid, R. Mohr, "Local greyvalue invariants for image retrieval", IEEE TPAMI, 19(5), 530-535, 1997.
23. C. Schmid, R. Mohr, C. Buackhage, "Evaluation of Interest Point Detectors", IJCV, 37(2), 151-172, 2000.
24. M. J. Swain, D. H. Ballard, "Color Indexing", IJCV, 7(1), 11-32, 1991.
25. V. Vapnik, Statistical learning theory, Wiley and sons, NY, 1998.
26. H. Bülthoff, C. Wallraven, A. Graf, "View-based dynamic recognition based on human perception", Proc. ICPR'02, 2002.