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Computer Vision Group
TUM Department of Informatics
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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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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