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Convex Optimizaton for Computer Vision
Tutorial DAGM 2011
Daniel Cremers & Thomas Pock
Content
- Introduction into convex optimization
- convex sets
- convex functions
least squares problems
linear programming problems
* Optimization algorithms
generic methods (gradient descend, Newton, ...)
constrained optimization
accelerated gradient methods
primal-dual algorithms
parallelization on the GPU
* Applications
image restoration
optical flow
the Mumford-Shah model
minimal partitions and minimal surfaces
3D reconstruction
Schedule
Tuesday, Aug. 30, 14-17:30
Slides
Coming shortly.
