Virtual line descriptor and semi-local matching method for reliable feature correspondence

BMVC 2012 - Electronic Proceedings of the British Machine Vision Conference 2012

Volumn , Issue , 2012, Pages

  Liu, Zhe ^a   Marlet, Renaud ^a  

^a UNIVERSITÉ PARIS EST   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERA CALIBRATION; DESCRIPTORS; FEATURE CORRESPONDENCE; LINE DESCRIPTOR; MATCHING METHODS; SECOND ORDERS; SETS OF FEATURES;

COMPUTER VISION;

EID: 84898454884     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.26.16     Document Type: Conference Paper

References (28)

1. A. Albarelli, E. Rodola, and A. Torsello. Robust game-theoretic inlier selection for bundle adjustment. In 3DPVT, 2010.
2. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Speeded-Up Robust Features (SURF). Computer Vision and Image Understanding, 110(3):346-359, 2008.
3. Alexander C. Berg, Tamara L. Berg, and Jitendra Malik. Shape matching and object recognition using low distortion correspondence. In CVPR, pages 26-33. IEEE, 2005.
4. M. Chertok and Y. Keller. Efficient high order matching. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 32(12):2205-2215, 2010.
5. Minsu Cho, Jungmin Lee, and Kyoung Mu Lee. Reweighted random walks for graph matching. In European Conference on Computer Vision (ECCV), pages 492-505, 2010.
6. Ondrej Chum and Jiri Matas. Matching with PROSAC - progressive sample consensus. In Conf. Computer Vision & Pattern Recognition (CVPR), pages 220-226. IEEE, 2005.
7. CMP, Czech Technical University, Prague. Dětenice fountain dataset, 2008. http://cmp.felk.cvut.cz/projects/is3d/Data.html.
8. D. Conte, P. Foggia, C. Sansone, and M. Vento. Thirty years of graph matching in pattern recognition. IJPRAI, 18:265-298, 2004.
9. Olivier Duchenne, Francis Bach, In-So Kweon, and Jean Ponce. A tensor-based algorithm for high-order graph matching. PAMI, 33(12):2383-2395, December 2011.
10. V. Ferrari, T. Tuytelaars, and L. Van Gool. Simultaneous object recognition and segmentation by image exploration. ECCV, pages 40-54, 2004.
11. M. A. Fischler and R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6):381-395, June 1981.
12. P. E. Forssén and D. G. Lowe. Shape descriptors for maximally stable extremal regions. In 11th IEEE Int'l Conference on Computer Vision (ICCV), pages 1-8. IEEE, 2007.
13. S. Gu, Y. Zheng, and C. Tomasi. Critical nets and beta-stable features for image matching. In European Conference on Computer Vision (ECCV), pages 663-676, 2010.
14. R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, second edition, 2004. ISBN 0521540518.
15. J. Lee, M. Cho, and K.M. Lee. Hyper-graph matching via reweighted random walks. In IEEE Conf. Computer Vision & Pattern Recognition (CVPR), pages 1633-1640, 2011.
16. M. Leordeanu and M. Hebert. A spectral technique for correspondence problems using pairwise constraints. In 10th ICCV, volume 2, pages 1482-1489. IEEE, 2005.
17. M. Leordeanu, R. Sukthankar, and M. Hebert. Unsupervised learning for graph matching. International Journal of Computer Vision (IJCV), 96(1):28-45, 2012.
18. D.G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision (IJCV), 60(2):91-110, 2004.
19. J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust wide-baseline stereo from maximally stable extremal regions. Image and Vision Computing, 22(10):761-767, 2004.
20. K. Mikolajczyk and C. Schmid. Scale & affine invariant interest point detectors. International Journal of Computer Vision (IJCV), 60(1):63-86, 2004.
21. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI), 27(10):1615-1630, October 2005.
22. L. Moisan and B. Stival. A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix. IJCV, 57(3):201-218, 2004.
23. L. Moisan, P. Moulon, and P. Monasse. Automatic homographic registration of a pair of images, with a contrario elimination of outliers. Image Processing On Line (IPOL), 2012. http://www.ipol.im/pub/algo/mmm-orsa-homography.
24. P. Ren, R. C. Wilson, and E. R. Hancock. High order structural matching using dominant cluster analysis. In Image Analysis and Processing (ICIAP), 2011.
25. C. Strecha, W. von Hansen, L. Van Gool, P. Fua, and U. Thoennessen. On benchmarking camera calibration and multi-view stereo for high resolution imagery. In Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
26. P. H. S. Torr and A. Zisserman. MLESAC: A new robust estimator with application to estimating image geometry. Computer Vision and Image Understanding, 78(1):138- 156, 2000.
27. A. Vedaldi and B. Fulkerson. VLFeat: An open and portable library of computer vision algorithms. In Int'l Conference on Multimedia, pages 1469-1472. ACM, 2010.
28. R. Zass and A. Shashua. Probabilistic graph and hypergraph matching. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.