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Convex Optimizaton for Computer Vision
Tutorial DAGM 2011
Daniel Cremers & Thomas Pock
Content
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.