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Discrete optimization methods in computer vision

Discrete optimization methods in computer vision. Nikos Komodakis Ecole Centrale Paris. ICCV 2007 tutorial. Rio de Janeiro Brazil, October 2007. Introduction: Discrete optimization and convex relaxations. (optimize an objective function). (subject to some constraints).

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562 views • 55 slides

Fast and accurate energy minimization for static or time-varying Markov Random Fields (MRFs)

Fast and accurate energy minimization for static or time-varying Markov Random Fields (MRFs). Nikos Komodakis (Ecole Centrale Paris) Nikos Paragios (Ecole Centrale Paris) Georgios Tziritas (University of Crete). vertices G = set of objects. edges E = object relationships.

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292 views • 21 slides

Fast, Approximately Optimal Solutions for Single and Dynamic Markov Random Fields (MRFs)

Fast, Approximately Optimal Solutions for Single and Dynamic Markov Random Fields (MRFs). Nikos Komodakis (Ecole Centrale Paris) Georgios Tziritas (University of Crete) Nikos Paragios (Ecole Centrale Paris). vertices G = set of objects. edges E = object relationships.

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283 views • 20 slides

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Dynamic mrfs - PowerPoint PPT Presentation

Discrete optimization methods in computer vision

Fast and accurate energy minimization for static or time-varying Markov Random Fields (MRFs)

Fast, Approximately Optimal Solutions for Single and Dynamic Markov Random Fields (MRFs)