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Pseudo-Boolean Optimization: Theory and Applications in Vision

På svenska

Author

  • Petter Strandmark
  • Fredrik Kahl

Summary, in English

Many problems in computer vision, such as stereo, segmentation and denoising can be formulated as pseudo-boolean optimization problems. Over the last decade, graphs cuts have become a standard tool for solving such problems. The last couple of years have seen a great advancement in the methods used to minimize pseudoboolean functions of higher order than quadratic. In this paper, we give an overview of how one can optimize higher-order functions via generalized roof duality and how it can be applied to problems in image analysis and vision.

Publishing year

2012

Language

English

Document type

Conference paper

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Conference name

Swedish Symposium on Image Analysis (SSBA) 2012

Conference date

2012-03-08 - 2012-03-09

Conference place

KTH, Stockholm, Sweden

Status

Unpublished

Research group

  • Mathematical Imaging Group