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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich



Variational Methods for Computer Vision

Tutorial ICCV 2011

Daniel Cremers, Bastian Goldlücke, Thomas Pock


  • Basic concepts of variational methods: variational approach, Euler-Lagrange equations, duality, …
  • Foundations of convex optimization and convex relaxation techniques
  • Optimal first-order algorithms for convex optimization
  • Variational formulations for classical computer vision problems: image segmentation, optical flow, stereo and multiview reconstruction, …
  • Relations to discrete optimization and Markov random fields
  • Mumford-Shah and multilabel problems
  • Numerical implementation and GPU acceleration

Schedule & Slides

Sunday, Nov. 6, Full day

9:30 - 10:15Mathematical FoundationsBastian Goldlücke
Coffee break
10:35 - 11:20Continuous Optimization in Computer VisionThomas Pock
Coffee break
11:40 - 12:25Variational Methods and Geometric ReconstructionDaniel Cremers
Lunch break
14:00 - 14:45Convex Relaxation for Motion and StereoThomas Pock
Coffee break
15:05 - 15:50Convex Relaxations for Multi-label ProblemsDaniel Cremers
Coffee break
16:10 - 16:55Vectorial Multilabel ProblemsBastian Goldlücke

Complete Slide Download

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Computer Vision Group

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