SVD-matching using SIFT features

Graphical Models

Volumn 68, Issue 5-6, 2006, Pages 415-431

  Delponte, Elisabetta ^a   Isgrò, Francesco ^a   Odone, Francesca ^a   Verri, Alessandro ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

Point matching; Scale invariant features; Spectral methods

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; GRAPHIC METHODS; IMAGE PROCESSING; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS);

POINT MATCHING; SCALE INVARIANT FEATURES; SPECTRAL METHODS;

PATTERN MATCHING;

ALGORITHM; COMPUTER VISION; IMAGE PROCESSING; SPECTRAL ANALYSIS;

EID: 33750492318     PISSN: 15240703     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.gmod.2006.07.002     Document Type: Article

References (47)

1. N. Allezard, M. Dhome, F. Jurie, Recognition of 3D textured objects by mixing view-based and model based representations, in: Proceedings of ICPR, 2000.
2. A. Baumberg, Reliable feature matching across widely separated views, in: Proceedings of CVPR, 2000, pp.774-781.
3. M. Brown, D. Lowe, Invariant features from interesting point groups, in: Proceedings of BMVC, 2002, pp. 656-665.
4. Carcassoni M., and Hancock E.R. Spectral correspondence for point pattern matching. Pattern Recognition 36 (2003) 193-204
5. Chung F.R. Spectral Graph Theory. American Mathematical Society vol,92 (1997)
6. Crowley J.L., and Parker A.C. A representation for shape based on peaks and ridges in the difference of low-pass transform. IEEE Transactions on Pattern Analysis and Machine Intelligence 6 2 (1984) 156-170
7. E. Delponte, F. Isgrò, F. Odone, A. Verri. SVD-matching using sift features. in: E. Trucco, M. Chantler, (Eds), Proceedings of the of the International Conference on Vision, Video and Graphics, pp 125-132, Edinburgh, UK, 2005, pp. 125-132.
8. R. Deriche, Z. Zhang, Q.T. Luong, O. Faugeras, Robust recovery of the epipolar geometry from an uncalibrated stereo rig. in: J.O. Eklundh, (Eds), Proceedings of ECCV, 1994, pp. 567-576.
9. S. Edelman, N. Ingrator, T. Poggio, Complex cells and object recognition. 1997. Unpublished manuscript. Cogprints.
10. V. Ferrari, T. Tuytelaars, L.V. Gool, Wide-baseline muliple-view correspondences. in: Proceedings of CVPR, 2003.
11. Freeman W., and Adelson E. The design and use of steerable filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 13 9 (1991) 891-906
12. M. Galun, E. Sharon, R. Basri, A. Brandt, Texture segmentation by multiscale aggregation of filter responses and shape elements, in: Proceedings of ICCV, 2003, pp. 716-723.
13. Georgis N., Petrou M., and Kittler J. On the correspondence problem for wide angular separation of non-coplanar points. Image and Vision Computing 16 (1998)
14. Golub G.H., and Loan C.F.V. Matrix Computations (1983), John Hopkins University Press
15. Hampel F.R., Ronchetti E.M., Rousseeuw P.J., and Stahel W.A. Robust Statistics: The Approach Based on Influence Functions (1986), John Wiley & Sons
16. C. Harris, Geometry from visual motion. in: A. Blake, A. Yuille (Eds), Active Vision, MIT Press, 1992.
17. C. Harris, M. Stephens, A combined corner and edge detector, in: Proceedings of the 4th Alvey Vision Conference, 1988, pp. 147-151.
18. Isgrò F., Trucco E., Kauff P., and Schreer O. Three-dimensional image processing in the future of immersive media. IEEE Transactions on Circuits and Systems for Video Technology 14 3 (2004) 288-303
19. T. Lindeberg, Principles for automatic scale selection, Technical Report ISRN KTH/NA/P-98/14-SE, CVAP Department of numerical analysis and computing science KTH, S-100 44 Stockholm, Sweden, August 1998.
20. Lindeberg T. Scale-space theory: a basic tool for analysing structures at different scales. Journal of Applied Statistics 21 2 (1994) 224-270
21. Lourakis M., Tzurbakis S., Argyros A., and Orphanoudakis S. Feature transfer and matching in disparate stereo views through the use of plane homographies. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 2 (2003)
22. Lowe D.G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60 2 (2004) 91-110
23. David G. Lowe, Object recognition from local scale-invariant features, in: Proceedings of ICCV, Corfu, Greece, 1999, pp. 1150-1157
24. Xiaoye Lu, R. Manduchi, wide-basline feature matching using the cross-epipolar ordering constraint, in: Proceedings of CVPR, 2004, pp. 16-23.
25. J. Matas, O. Chum, M. Urban, T. Pajdla, Robust wide baseline stereo from maximally stable extremal regions, in: Proceedings of BMVC, 2002, pp. 384-393.
26. K. Mikolajczyk, C. Schmid, A performance evaluation of local descriptors, in: Proceedings of CVPR, 2003, pp. 257-263.
27. Mikolajczyk K., and Schmid C. Scale and affine invariant interest point detectors. International Journal of Computer Vision 60 1 (2004) 63-86
28. H. Moravec, Rover visual obstacle avoidance, in: Proc. of the 7th Intern, Joint Conference on Artificial Intelligence, 1981, pp. 785-790.
29. M. Pilu, A direct method for stereo correspondence based on singular value decomposition, in: Proceedings of CVPR, Puerto Rico, 1997, pp. 261-266.
30. P. Pritchett, A. Zisserman, Wide baseline stereo matching, in: Proceedings of ICCV, 1998, pp. 754-760.
31. Rosenfeld A., and van der Brug G. Coarse-fine template matching. IEEE Transactions on Systems, Man and Cybernetics 7 (1977) 104-107
32. Schmid C., and Mohr R. Local grayvalue invariants for image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 5 (1997) 530-534
33. Schmid C., Mohr R., and Bauckhage C. Evaluation of interest point detectors. International Journal of Computer Vision 37 2 (2000) 151-172
34. C. Schmid, A. Zissermann, Automatic line matching across views. in: Proceedings of CVPR, (1997)666-671.
35. Sclaroff S., and Pentland A.P. Modal matching for correspondence and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 17 6 (1995) 545-561
36. Scott G., and Longuet-Higgins H. An algorithm for associating the features of two images. Proceedings of Royal Society London B244 (1991) 21-26
37. Shapiro L.S., and Brady J.M. Feature-based correspondence - an eigenvector approach. Image Vision Computing 10 (1992)
38. J. Shi, C. Tomasi, Good features to track. in: Proceedings of CVPR, 1994, pp. 593-600
39. Shokoufandeh A., Marsic I., and Dickinson S.J. View-based object recognition using saliency maps. Image and Vision Computing 17 (1999) 445-460
40. D. Tell, S. Carlsson, Combining appearance and topology for wide baseline matching. in: Proceedings of ECCV, 2002, pp. 68-81.
41. Trucco E., and Verri A. Introductory Techniques for 3-D Computer Vision (1998), Prentice-Hall
42. T. Tuytelaars, L.V. Gool. Wide baseline stereo matching based on local, affinely invariant regions, in: Proceedings of BMVC, 2000, pp. 412-425.
43. Umeyama S. An eigen decomposition approach to weighted graph matching problems. IEEE Transactions on Pattern Analysis and Machine Intelligence 10 (1988)
44. van der Brug G., and Rosenfeld A. Two-stage template matching. IEEE Transactions on Computers 26 4 (1977) 384-393
45. Y. Weiss, Segmentation using eigenvectors: a unifying view. In Proceedings of ICCV, pages 975-982, 1999.
46. R. Zabih, J. Woodfill. Non-parametric local transforms for computing visual corresposdence. In Proceedings of ECCV, pages 151-158, 1994.
47. Zhang Z., Deriche R., Faugeras O., and Luong Q.T. A robust techique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. Artificial Intelligence 78 (1995) 87-119