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Volumn 6315 LNCS, Issue PART 5, 2010, Pages 225-238

Convex relaxation for multilabel problems with product label spaces

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; OPTICAL FLOWS; STEREO IMAGE PROCESSING;

EID: 78149333144     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15555-0_17     Document Type: Conference Paper
Times cited : (20)

References (21)
  • 2
    • 33750153530 scopus 로고    scopus 로고
    • Algorithms for finding global minimizers of image segmentation and denoising models
    • DOI 10.1137/040615286
    • Nikolova, M., Esedoglu, S., Chan, T.: Algorithms for finding global minimizers of image segmentation and denoising models. SIAM Journal of Applied Mathematics 66, 1632-1648 (2006) (Pubitemid 44599935)
    • (2006) SIAM Journal on Applied Mathematics , vol.66 , Issue.5 , pp. 1632-1648
    • Chan, T.F.1    Esedoglu, S.2    Nikolova, M.3
  • 3
    • 56749157676 scopus 로고    scopus 로고
    • A convex formulation of continuous multi-label problems
    • Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. Springer, Heidelberg
    • Pock, T., Schoenemann, T., Graber, G., Bischof, H., Cremers, D.: A convex formulation of continuous multi-label problems. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 792-805. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5304 , pp. 792-805
    • Pock, T.1    Schoenemann, T.2    Graber, G.3    Bischof, H.4    Cremers, D.5
  • 6
    • 0000169287 scopus 로고
    • Bayesian modeling of uncertainty in low-level vision
    • Szeliski, R.: Bayesian modeling of uncertainty in low-level vision. International Journal of Computer Vision 5, 271-301 (1990)
    • (1990) International Journal of Computer Vision , vol.5 , pp. 271-301
    • Szeliski, R.1
  • 9
    • 0000111836 scopus 로고
    • Exact maximum a posteriori estimation for binary images
    • Greig, D., Porteous, B., Seheult, A.: Exact maximum a posteriori estimation for binary images. J. Royal Statistics Soc. 51, 271-279 (1989)
    • (1989) J. Royal Statistics Soc. , vol.51 , pp. 271-279
    • Greig, D.1    Porteous, B.2    Seheult, A.3
  • 13
    • 27744456278 scopus 로고    scopus 로고
    • Map estimation via agreement on trees: Message-passing and linear programming
    • Wainwright, M., Jaakkola, T., Willsky, A.: Map estimation via agreement on trees: message-passing and linear programming. IEEE Trans. Inf. Theory 51, 3697-3717 (2005)
    • (2005) IEEE Trans. Inf. Theory , vol.51 , pp. 3697-3717
    • Wainwright, M.1    Jaakkola, T.2    Willsky, A.3
  • 14
    • 0142039762 scopus 로고    scopus 로고
    • Exact optimization for markov random fields with convex priors
    • Ishikawa, H.: Exact optimization for markov random fields with convex priors. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1333-1336 (2003)
    • (2003) IEEE Trans. Pattern Anal. Mach. Intell. , vol.25 , pp. 1333-1336
    • Ishikawa, H.1
  • 15
    • 56749131672 scopus 로고    scopus 로고
    • An experimental comparison of discrete and continuous shape optimization methods
    • Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. Springer, Heidelberg
    • Klodt, M., Schoenemann, T., Kolev, K., Schikora, M., Cremers, D.: An experimental comparison of discrete and continuous shape optimization methods. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 332-345. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5302 , pp. 332-345
    • Klodt, M.1    Schoenemann, T.2    Kolev, K.3    Schikora, M.4    Cremers, D.5
  • 16
    • 34250242132 scopus 로고
    • A modification of the arrow-hurwicz method for search of saddle points
    • Popov, L.: A modification of the arrow-hurwicz method for search of saddle points. Math. Notes 28, 845-848 (1980)
    • (1980) Math. Notes , vol.28 , pp. 845-848
    • Popov, L.1
  • 17
    • 17444406259 scopus 로고    scopus 로고
    • Smooth minimization of non-smooth functions
    • Nesterov, Y.: Smooth minimization of non-smooth functions. Math. Prog. 103, 127-152 (2004)
    • (2004) Math. Prog. , vol.103 , pp. 127-152
    • Nesterov, Y.1
  • 18
    • 85014561619 scopus 로고    scopus 로고
    • Fast iterative shrinkage-thresholding algorithm for linear inverse problems
    • Beck, A., Teboulle, M.: Fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sciences 2, 183-202 (2009)
    • (2009) SIAM J. Imaging Sciences , vol.2 , pp. 183-202
    • Beck, A.1    Teboulle, M.2
  • 19
    • 38349007037 scopus 로고    scopus 로고
    • 1 optical flow
    • Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM2007. Springer, Heidelberg
    • 1 optical flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM2007. LNCS, vol. 4713, pp. 214-223. Springer, Heidelberg (2007)
    • (2007) LNCS , vol.4713 , pp. 214-223
    • Zach, C.1    Pock, T.2    Bischof, H.3
  • 20
    • 69049110196 scopus 로고    scopus 로고
    • Projected gradient based color image decomposition
    • Tai, X.-C., Mørken, K., Lysaker, M., Lie, K.-A. (eds.) Scale Space and Variational Methods in Computer Vision. Springer, Heidelberg
    • Duval, V., Aujol, J.F., Vese, L.: Projected gradient based color image decomposition. In: Tai, X.-C., Mørken, K., Lysaker, M., Lie, K.-A. (eds.) Scale Space and Variational Methods in Computer Vision. LNCS, vol. 5567, pp. 295-306. Springer, Heidelberg (2009)
    • (2009) LNCS , vol.5567 , pp. 295-306
    • Duval, V.1    Aujol, J.F.2    Vese, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.