TV-L1 Optical Flow Estimation
Image Processing On Line2013Vol. 3, pp. 137–150
Citations Over TimeTop 1% of 2013 papers
Abstract
This article describes an implementation of the optical flow estimation method introduced by Zach, Pock and Bischof in 2007. This method is based on the minimization of a functional containing a data term using the L1 norm and a regularization term using the total variation of the flow. The main feature of this formulation is that it allows discontinuities in the flow field, while being more robust to noise than the classical approach of Horn and Schunck. The algorithm is an efficient numerical scheme, which solves a relaxed version of the problem by alternate minimization.
Related Papers
- → Locally Adaptive Total Variation Regularization(2009)65 cited
- → Spatially dependent regularization parameter selection for total generalized variation-based image denoising(2016)14 cited
- → An Efficient Algorithm for Total Variation Denoising(2017)9 cited
- → A fast one dimensional total variation regularization algorithm(2017)4 cited
- → Image Denoising Via Spatially Adaptive Directional Total Generalized Variation(2022)2 cited