Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Performance of optical flow techniques
International Journal of Computer Vision
SIAM Journal on Scientific Computing
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Symmetrical Dense Optical Flow Estimation with Occlusions Detection
International Journal of Computer Vision
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Can Variational Models for Correspondence Problems Benefit from Upwind Discretisations?
Journal of Mathematical Imaging and Vision
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Variational approaches to correspondence problems such as stereo or optic flow have now been studied for more than 20 years. Nevertheless, only little attention has been paid to a subtle numerical approximation of derivatives. In the area of numerics for hyperbolic partial differential equations (HDEs) it is, however, well-known that such issues can be crucial for obtaining favourable results. In this paper we show that the use of hyperbolic numerics for variational approaches can lead to a significant quality gain in computational results. This improvement can be of the same order as obtained by introducing better models. Applying our novel scheme within existing variational models for stereo reconstruction and optic flow, we show that this approach can be beneficial for all variational approaches to correspondence problems.