Community detection for hierarchical image segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6636 LNCS, Issue , 2011, Pages 358-371

  Browet, Arnaud ^a   Absil, P A ^a   Van Dooren, Paul ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

community detection; Image segmentation; modularity optimization

Indexed keywords

COMMUNITY DETECTION; COMMUNITY STRUCTURES; GRAPH-BASED TECHNIQUES; LARGE GRAPHS; MODULARITY OPTIMIZATION; PRIORI KNOWLEDGE; REAL IMAGES;

APPROXIMATION ALGORITHMS; IMAGE ANALYSIS; OPTIMIZATION; POPULATION DYNAMICS;

IMAGE SEGMENTATION;

EID: 79957646607     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21073-0_32     Document Type: Conference Paper

References (22)

1. Alzate, C., Suykens, J.A.K.: Sparse kernel models for spectral clustering using the incomplete cholesky decomposition. In: IJCNN, pp. 3556-3563 (2008)
2. Alzoubi, H., Pan, W.D.: Fast and accurate global motion estimation algorithm using pixel subsampling. Information Sciences 178(17), 3415 (2008)
3. Beucher, S.: The watershed transformation applied to image segmentation (1991)
4. Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008(10), 10008 (2008)
5. Cox, I., Rao, S., Zhong, Y.: "ratio regions": A technique for image segmentation. In: International Conference on Pattern Recognition, vol. 2, p. 557 (1996)
6. Delvenne, J.C., Yaliraki, S.N., Barahona, M.: Stability of graph communities across time scales. PNAS 107(29), 12755-12760 (2010)
7. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. Int. J. Comput. Vision 59, 167-181 (2004)
8. Fortunato, S.: Community detection in graphs. Physics Reports (2010)
9. Frederix, K., Barel, M.V.: Sparse spectral clustering method based on the incomplete cholesky decomposition. Report TW552, Katholieke Universiteit Leuven (2009)
10. Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America 99(12), 7821-7826 (2002) (Pubitemid 34650963)
11. Good, B.H., de Montjoye, Y.A., Clauset, A.: Performance of modularity maximization in practical contexts. Physical Review E 81(4), 046106+ (2010)
12. Ho, J., Lee, K.C., Yang, M.H., Kriegman, D.: Visual tracking using learned linear subspaces. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. I-782-I-789 (2004)
13. Olszewska, J.I.: Unified framework for multi-feature active contour. Ph.D. thesis, Universite catholique de Louvain, Ecole polytechnique (2009)
14. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321-331 (1988), doi:10.1007/BF00133570
15. Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proc. 8th Int'l Conf. Computer Vision, vol. 2, pp. 416-423 (2001) (Pubitemid 32795086)
16. Newman, M.E., Girvan, M.: Finding and evaluating community structure in networks. Physical review. E, Statistical, nonlinear, and soft matter physics 69(2 Pt 2) (2004)
17. Reichardt, J., Bornholdt, S.: Statistical mechanics of community detection. Phys. Rev. E. Stat. Nonlin. Soft Matter Phys. 74(1 Pt 2) (2006)
18. Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8), 888-905 (2000)
19. Sundaramoorthi, G., Mennucci, A., Soatto, S., Yezzi, A.: Tracking deforming objects by filtering and prediction in the space of curves. In: CDC (December 2009)
20. Wang, S., Siskind, J.M.: Image segmentation with minimum mean cut. In: Proceedings of the Eighth IEEE International Conference on Computer Vision, ICCV 2001, vol. 1, pp. 517-524 (2001) (Pubitemid 32794997)
21. Werman, M., Peleg, S., Rosenfeld, A.: A distance metric for multidimensional histograms. Computer Vision, Graphics, and Image Processing 32(3), 328-336 (1985)
22. Wu, Z., Leahy, R.: An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(11), 1101-1113 (2002)