Markov+Random+Field

**
 * Markov Random Field toc


 * 1) =** Introduction/Tutorial **=
 * MRF in Wikipedia
 * 1) = **Applications** =
 * 2) Image Inpainting
 * [|Digital Image Inpainting based on MRF, IEEE Int. Conf. on Computational Intelligence for Modeling, Control and Automation, 2005].
 * [|Image Inpainting Using Particle Filters and MRF],.
 * 1) Image Segmentation
 * 2) = Algorithm (Energy Minimization) =
 * 3) ==[|Graph Cut] ==
 * ECCV06_tutorial
 * ICCV07_tutorial
 * An Experimental Comparison of Min-Cut_Max-Flow Algorithms for Energy Minimization in Vision
 * Motion Layer Extraction in the Presence of Occlusion Using Graph Cuts
 * 1) == ICM ==
 * Iterative Conditional Modes
 * 1) == **[|Belief Propagation]** ==
 * Also called Max-Product/Min-Sum Algorithm.
 * Comparing the mean field method and belief propagation for approximate inference in MRFs, Weiss Y. To appear in Saad and Opper (ed) Advanced Mean Field Methods. MIT Press. [|(gzipped postscript 89K)]
 * 1) = **Library/Open Source** =
 * 2) == **Graph Cut Optimization** ==
 * **Max-Flow/Min-Cut**
 * **Program information: [|MaxFlow-v3.01.zip] ,** C/C++ source, Ver. 3.01, 2010/01
 * **Reference papers**: [|Boykov-Kolmogorov algorithm], B-K algorithm Yuri Boykov and Vladimir Kolmogorov, "An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision," //IEEE Trans. Pattern Analysis and Machine Intelligence//, vol. 24, no. 9, pp. 1124-1137, 2004.
 * **Implementated methods:** Graph Cut
 * **Multi-Label Optimization**
 * **Program information**: **[|gco-v3.0.zip], C/C++ source with Matlab wrapper, Ver. 3.0, 2010/08**
 * **Reference papers**:
 * ** Y. Boykov, O. Veksler, R. Zabin, "Fast Approximate Energy Minimization via Graph Cuts," //IEEE Trans. Pattern Analysis and Machine Intelligence//, vol. 23, no. 11, pp. 1222-1239, 2001. **
 * ** Yuri Boykov and Vladimir Kolmogorov, "An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision," //IEEE Trans. Pattern Analysis and Machine Intelligence//, vol. 24, no. 9, pp. 1124-1137, 2004. **
 * ** Andrew Delong · Anton Osokin · Hossam N. Isack · Yuri Boykov, "Fast Approximate Energy Minimization with Label Costs" //International Journal of Computer Vision//, 2011. **
 * ** Vladimir Kolmogorov, Ramin Zabih, "What Energy Functions Can Be Minimized via Graph Cuts?" //IEEE Trans. Pattern Analysis and Machine Intelligence//, vol. 26, no. 2, pp. 147-158, 2004. **
 * **Implementated methods:** Graph Cut
 * [|Middlebury MRF]
 * **Program information:** [|MRF16.zip] : C/C++, Ver. 1.6, 2006
 * **Reference papers:** [|A Comparative Study of Energy Minimization Methods for Markov Random Fields] R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother. In //Ninth European Conference on Computer Vision//(ECCV 2006), volume 2, pages 19-26, Graz, Austria, May 2006.
 * **Implementated methods:** ICM, Graph Cut, Max-Product Belief Propagation
 * Misc
 * [|James Malcom] : Graph cut for image segmentation and multi-object tracking, Matlab wrapper witout source code.
 * 1) =Books=
 * Markov Random Field Modeling in Image Analysis, S. Z. Li, Springer, 2001.
 * Stochastic Image Processing, C. S. Won and R. M. Gray, Kluwer, 2004.
 * Image Analysis, Random Fields and Dynamic Monte Carlo Methods, - A Mathematical Introduction, G. Winkler, Springer, 1995.
 * Markov Random Fields - Theory and Application, R. Chellappa and A. Jain, Academic Press, 1993.
 * Markov Random Fields - Theory and Application, R. Chellappa and A. Jain, Academic Press, 1993.