Computer Vision and Image Understanding, Special issue on Optimization for vision, graphics and medical imaging: Theory and applications

Abstract : A wide array of problems in Visual Computing can be naturally formulated as optimization tasks. In this context one wants to optimize an objective function that measures how well a set of hidden parameters fits to the observed visual data. The popularity of these approaches stems from the fact that most processes related to Visual Computing are typically characterized by a lack of closed form solutions, and uncertainties (due to noise, imperfect sensors, ambiguities in the visual interpretation etc.). As a result perfect or exact solutions hardly exist, whereas inexact but optimal (in an application-specific sense) solutions and their efficient computation is what one aims at. Computer vision, computer graphics and medical imaging are three areas of Visual Computing for which the optimization paradigm has gained a significant interest within the last years, largely due to the development of highly efficient and sophisticated optimization techniques, which are capable of handling large scale problems with complex objective functions. In this special issue we are soliciting papers from all the above mentioned fields that present new theoretical contributions as well as interesting applications of optimization methods.
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Submitted on : Thursday, September 5, 2013 - 1:38:16 PM
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Nikos Komodakis, Georg Langs, Horst Bischof, Nikos Paragios. Computer Vision and Image Understanding, Special issue on Optimization for vision, graphics and medical imaging: Theory and applications. Elsevier, pp.1597, 2011. ⟨hal-00858406⟩

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