'Min marginals' diaporamas de présentation

Discrete Optimization Lecture 8

Discrete Optimization Lecture 8. M. Pawan Kumar pawan.kumar@ecp.fr. Slides available online http:// cvn.ecp.fr /personnel/ pawan /. Recap !!. Questions?. Energy Minimization. 0. 6. 1. 3. 2. 0. 4. Label l 1. 1. 2. 3. 4. 1. 1. Label l 0. 1. 0. 5. 0. 3. 7. 2. V b. V c.

1.23k views • 107 slides

Discrete Optimization Lecture 2

Discrete Optimization Lecture 2. M. Pawan Kumar pawan.kumar@ecp.fr. Image Segmentation. How ?. Cost/Energy function. Models our knowledge about natural images. Optimize energy function to obtain the segmentation. Image Segmentation. Graph G = (V,E).

934 views • 74 slides

Measuring Uncertainty in Graph Cut Solutions

Measuring Uncertainty in Graph Cut Solutions. Pushmeet Kohli Philip H.S. Torr Department of Computing Oxford Brookes University. st-mincut. Most Probable Solution. s. t. Labelling problem. Objective. Graph Cut. No uncertainty measure associated with the solution.

941 views • 73 slides

Measuring Uncertainty in Graph Cut Solutions

Measuring Uncertainty in Graph Cut Solutions. Pushmeet Kohli Philip H.S. Torr Department of Computing Oxford Brookes University. st-mincut. Most Probable Solution. s. t. Labelling problem. Objective. Graph Cut. No uncertainty measure associated with the solution.

738 views • 73 slides

ICCV 2007 tutorial Part III Message-passing algorithms for energy minimization

ICCV 2007 tutorial Part III Message-passing algorithms for energy minimization. Vladimir Kolmogorov University College London. Message passing. q. p. Iteratively pass messages between nodes... Message update rule? Belief propagation (BP) Tree-reweighted belief propagation (TRW)

444 views • 44 slides

518 views • 36 slides