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Advanced Belief Propagation Methods in Vision

Discover state-of-the-art efficient belief propagation techniques for vision applications using linear constraint nodes. Explore our method's progress with Mean Squared Error at 102 and ongoing developments on parameter learning for the MRF model. Future plans include collaborating with Dr. Tappen in the Fall and documenting math derivations in LaTex.

karina-robertson
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Advanced Belief Propagation Methods in Vision

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  1. UCF Week 12 REU Lam Tran

  2. State of The Art Efficient Belief Propagation for Vision Using Linear Constraint Nodes, Brian Potetz (CMU) CVPR 07 - 5 citations and they are not related to shape from shading.

  3. Our Result Our Method: Mean Squared Error = 102

  4. In Progress • Still working on learning the parameters for our MRF. • Writing up math derivation in LaTex

  5. Future Plans • Continue to work with Dr. Tappen in the Fall.

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