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Optimization of Markov Random Fields in Computer Vision

Ajanthan, Thalaiyasingam

Description

A large variety of computer vision tasks can be formulated using Markov Random Fields (MRF). Except in certain special cases, optimizing an MRF is intractable, due to a large number of variables and complex dependencies between them. In this thesis, we present new algorithms to perform inference in MRFs, that are either more efficient (in terms of running time and/or memory usage) or more effective (in terms of solution quality), than the state-of-the-art...[Show more]

CollectionsOpen Access Theses
Date published: 2017
Type: Thesis (PhD)
URI: http://hdl.handle.net/1885/137281

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