Sub-markov random walk for image segmentation

IEEE Transactions on Image Processing

Volumn 25, Issue 2, 2016, Pages 516-527

  Dong, Xingping ^a   Shen, Jianbing ^a   Shao, Ling ^b   Van Gool, Luc ^c  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b NORTHUMBRIA UNIVERSITY   (United Kingdom)

^c ETH ZURICH   (Switzerland)

Author keywords

Complex texture; Label prior; Optimization; Random walk; Seeded image segmentation; SubMarkov

Indexed keywords

OPTIMIZATION; RANDOM PROCESSES;

NATURAL IMAGES; RANDOM WALK; RANDOM WALKERS; SUBMARKOV;

IMAGE SEGMENTATION;

EID: 85009399339     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2015.2505184     Document Type: Article

References (43)

1. H. Wechsler and M. Kidode, "A random walk procedure for texture discrimination," IEEE Trans. Pattern Anal. Mach. Intell., vol. 1, no. 3, pp. 272-280, Jul. 1979.
2. R. A. Horn and C. R. Johnson, Matrix Analysis. Cambridge, U.K.: Cambridge Univ. Press, 1985.
3. J. J. Dongarra, I. S. Duff, D. C. Sorensen, and H. A. Van Der Vorst, Solving Linear Systems on Vector and Shared Memory Computers. Philadelphia, PA, USA: SIAM, 1991.
4. W. Hackbusch, Iterative Solution of Large Sparse Systems of Equations. Springer-Verlag, 1994.
5. G. H. Golub and C. F. van Loan, Matrix Computations, 3rd ed. Baltimore, MD, USA: The Johns Hopkins Univ. Press, 1996.
6. F. R. Chung, Spectral Graph Theory, vol. 92. Providence, RI, USA: AMS, 1997.
7. L. Page, S. Brin, R. Motwani, and T. Winograd, "The PageRank citation ranking: Bringing order to the Web," Tech. Rep., 1999.
8. J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 8, pp. 888-905, Aug. 2000.
9. D. Martin, C. Fowlkes, D. Tal, and J. Malik, "A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics," in Proc. IEEE ICCV, Jul. 2001, pp. 416-423.
10. T. Jaakkola and M. Szummer, "Partially labeled classification with Markov random walks," in Proc. NIPS, vol. 14. 2002, pp. 945-952.
11. X. Zhu, Z. Ghahramani, and J. Lafferty, "Semi-supervised learning using Gaussian fields and harmonic functions," in Proc. 12th ICML, vol. 3. 2003, pp. 912-919.
12. D. Zhou and B. Schölkopf, "Learning from labeled and unlabeled data using random walks," in Proc. 26th DAGM Symp., 2004, pp. 237-244.
13. J.-Y. Pan, H.-J. Yang, C. Faloutsos, and P. Duygulu, "Automatic multimedia cross-modal correlation discovery," in Proc. ACM SIGKDD, 2004, pp. 653-658.
14. J. Ham, D. D. Lee, S. Mika, and B. Schölkopf, "A kernel view of the dimensionality reduction of manifolds," in Proc. IEEE ICML, 2004, pp. 1-9.
15. L. Grady and G. Funka-Lea, "Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials," in Proc. ECCV Workshops CVAMIA MMBIA, 2004, pp. 230-245.
16. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf, "Learning with local and global consistency," in Proc. NIPS, 2004, pp. 321-328.
17. L. Grady, "Multilabel random walker image segmentation using prior models," in Proc. IEEE CVPR, Jun. 2005, pp. 763-770.
18. M. Gori, M. Maggini, and L. Sarti, "Exact and approximate graph matching using random walks," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 7, pp. 1100-1111, Jun. 2005.
19. L. Yen, D. Vanvyve, F. Wouters, F. Fouss, M. Verleysen, and M. Saerens, "Clustering using a random walk based distance measure," in Proc. 13th Eur. Symp. Artif. Neural Netw., 2005, pp. 317-324.
20. L. Grady, "Random walks for image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 11, pp. 1768-1783, Nov. 2006.
21. L. Grady and E. L. Schwartz, "Isoperimetric graph partitioning for image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 3, pp. 469-475, Mar. 2006.
22. H. Tong, C. Faloutsos, and J.-Y. Pan, "Fast random walk with restart and its applications," in Proc. ICDM, 2006, pp. 613-622.
23. A. K. Sinop and L. Grady, "A seeded image segmentation framework unifying graph cuts and random walker which yields a new algorithm," in Proc. IEEE ICCV, Oct. 2007, pp. 1-8.
24. S. Calinon, F. Guenter, and A. Billard, "On learning, representing, and generalizing a task in a humanoid robot," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 37, no. 2, pp. 286-298, Apr. 2007.
25. H. Qiu and E. R. Hancock, "Clustering and embedding using commute times," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 11, pp. 1873-1890, Nov. 2007.
26. F. Fouss, A. Pirotte, J.-M. Renders, and M. Saerens, "Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation," IEEE Trans. Knowl. Data Eng., vol. 19, no. 3, pp. 355-369, Mar. 2007.
27. T. H. Kim, K. M. Lee, and S. U. Lee, "Generative image segmentation using random walks with restart," in Proc. ECCV, 2008, pp. 264-275.
28. L. Grady and A. K. Sinop, "Fast approximate random walker segmentation using eigenvector precomputation," in Proc. IEEE CVPR, Jun. 2008, pp. 1-8.
29. J. Wang, F. Wang, C. Zhang, H. C. Shen, and L. Quan, "Linear neighborhood propagation and its applications," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 9, pp. 1600-1615, Sep. 2009.
30. G. F. Lawler and V. Limic, Random Walk: A Modern Introduction. Cambridge, U.K.: Cambridge Univ. Press, 2010.
31. Q. Mei, J. Guo, and D. Radev, "DivRank: The interplay of prestige and diversity in information networks," in Proc. ACM KDD, 2010, pp. 1009-1018.
32. U. von Luxburg, A. Radl, and M. Hein. (2010). "Hitting and commute times in large graphs are often misleading." [Online]. Available: http://arxiv.org/abs/1003.1266
33. V. Gopalakrishnan, Y. Hu, and D. Rajan, "Random walks on graphs for salient object detection in images," IEEE Trans. Image Process., vol. 19, no. 12, pp. 3232-3242, Dec. 2010.
34. L. J. Grady and J. Polimeni, Discrete Calculus: Applied Analysis on Graphs for Computational Science. Springer, 2010.
35. C. Couprie, L. Grady, L. Najman, and H. Talbot, "Power watershed: A unifying graph-based optimization framework," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 7, pp. 1384-1399, Jul. 2011.
36. S. Jegelka and J. Bilmes, "Submodularity beyond submodular energies: Coupling edges in graph cuts," in Proc. IEEE CVPR, Jun. 2011, pp. 1897-1904.
37. X.-M. Wu, Z. Li, A. M. So, J. Wright, and S.-F. Chang, "Learning with partially absorbing random walks," in Proc. NIPS, 2012, pp. 3077-3085.
38. P. Kohli, A. Osokin, and S. Jegelka, "A principled deep random field model for image segmentation," in Proc. IEEE CVPR, Jun. 2013, pp. 1971-1978.
39. B. Ham, D. Min, and K. Sohn, "A generalized random walk with restart and its application in depth up-sampling and interactive segmentation," IEEE Trans. Image Process., vol. 22, no. 7, pp. 2574-2588, Jul. 2013.
40. J. Shen, Y. Du, W Wang, and X. Li, "Lazy random walks for superpixel segmentation," IEEE Trans. Image Process., vol. 23, no. 4, pp. 1451-1462, Apr. 2014.
41. X. Zhu, W Nejdl, and M. Georgescu, "An adaptive teleportation random walk model for learning social tag relevance," in Proc. ACM SIGIR, 2014, pp. 223-232.
42. A. Sironi, V. Lepetit, and P. Fua, "Multiscale centerline detection by learning a scale-space distance transform," in Proc. IEEE CVPR, Jun. 2014, pp. 2697-2704.
43. X. Dong, J. Shen, and L. Van Gool, "Segmentation using subMarkov random walk," in Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer, 2015, pp. 237-248.