An Efficient Linearisation Approach for Variational Perspective Shape from Shading

Maurer, Daniel; Ju, Yong Chul; Breuß, Michael; Bruhn, Andrés

doi:10.1007/978-3-319-24947-6_20

Cited by 1 publication

(1 citation statement)

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“…In many cases such correspondences are not unique or simply fail to exist because of various problems such as noise, illumination changes and overlapping objects. Nevertheless, the study of the OF problem is of fundamental importance for dealing with correspondence problems such as stereo vision where accurate flow fields are necessary [3,39,40,57]. For solving the OF problem in a robust way, variational formulations and regularisation strategies belong to the most successful techniques.…”

Section: The Optical Flow Problemmentioning

confidence: 99%

Bregman Iteration for Correspondence Problems: A Study of Optical Flow

Hoeltgen¹,

Breuß²

2015

Preprint

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Bregman iterations are known to yield excellent results for denoising, deblurring and compressed sensing tasks, but so far this technique has rarely been used for other image processing problems. In this paper we give a thorough description of the Bregman iteration, unifying thereby results of different authors within a common framework. Then we show how to adapt the split Bregman iteration, originally developed by Goldstein and Osher for image restoration purposes, to optical flow which is a fundamental correspondence problem in computer vision. We consider some classic and modern optical flow models and present detailed algorithms that exhibit the benefits of the Bregman iteration. By making use of the results of the Bregman framework, we address the issues of convergence and error estimation for the algorithms. Numerical examples complement the theoretical part.

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Section: The Optical Flow Problemmentioning

confidence: 99%