Capacity scaling for graph cuts in vision

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Juan, Olivier ^a   Boykov, Yuri ^a  

^a UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; COMBINATORIAL MATHEMATICS; COMBINATORIAL OPTIMIZATION; COMPUTER NETWORKS; COMPUTER VISION; IMAGE PROCESSING; IMAGE SEGMENTATION; OPTIMIZATION; POLYNOMIAL APPROXIMATION; POLYNOMIALS;

CAPACITY SCALING;

COMPUTATIONAL GEOMETRY;

EID: 50649084723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4408970     Document Type: Conference Paper

References (18)

1. Y. Boykov and G. Funka-Lea. Graph cuts and efficient n-d image segmentation. Int. J. Comput. Vision, 70(2):109-131, 2006.
2. Y. Boykov and V. Kolmogorov. Computing geodesics and minimal surfaces via graph cuts. In IEEE International Conference on Computer Vision, volume 1, pages 26-33, Washington, DC, USA, 2003.
3. Y. Boykov and V. Kolmogorov. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans. Pattern Anal. Mach. Intell., 26(9):1124-1137, sept. 2004.
4. Y. Boykov and V. Lempitsky. From photohulls to photoflux optimization. In British Machine Vision Conference, volume 3, pages 1149-1158, Edinburgh, UK, Sept. 2006.
5. Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell., 23(11):1222-1239, 2001.
6. E. A. Dinic. Metod porazryadnogo sokrashcheniya nevyazok i transportnye zadachi. Issledovaniya po Diskretnoi Maternatike, Science, 1973. Title translation: The Method of Scaling and Transportation Problems.
7. J. Edmonds and R. M. Karp. Theoretical improvements in algorithmic efficiency for network flow problems. Journal of the Association for Computing Machinery, 19(2):248-264, 1972.
8. L. R. Ford and D. R. Fulkerson. Flows in Networks. Princeton University Press, june 1962.
9. D. S. Hochbaum. The pseudoflow algorithm: A new algorithm for the maximum flow problem. Long version of same titled paper, may 2004.
10. O. Juan and Y. Boykov. Active graph cuts. In IEEE Conference on Computer Vision and Pattern Recognition, june 2006. New York.
11. O. Juan and Y. Boykov. Capacity scaling for graph cuts in vision. Technical report, University ofWestern Ontario, august 2007.
12. P. Kohli and P. H. Torr. Efficiently solving dynamic markov random fields using graph cuts. In IEEE International Conference on Computer Vision, volume 2, pages 922-929, 2005.
13. V. Kolmogorov and Y. Boykov. What metrics can be approximated by geo-cuts, or global optimization of length/area and flux. In IEEE Inter. Conf. on Comp. Vision, volume 1, pages 564-571, Washington, DC, USA, 2005.
14. V. Kolmogorov and C. Rother. Minimizing non-submodular functions with graph cuts - a review. IEEE Trans. Pattern Anal. Mach. Intell., 2007. (to appear).
15. V. Kolmogorov and R. Zabih. What energy functions can be minimized via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell., 26(2):147-159, February 2004.
16. H. Lombaert, Y. Sun, L. Grady, and C. Xu. A multilevel banded graph cuts method for fast image segmentation. In IEEE International Conference on Computer Vision, volume 1, pages 259-265, Washington, DC, USA, 2005.
17. C. Rother, V. Kolmogorov, and A. Blake. Grabcut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph., 23(3):309-314, 2004.
18. G. Vogiatzis, P. H. S. Torr, and R. Cipolla. Multi-view stereo via volumetric graph-cuts. In IEEE Comp. Soc. Conf. on Comp. Vision and Pattern Recog., volume 2, pages 391-398, Washington, DC, USA, 2005.