Performance of optical flow techniques
International Journal of Computer Vision
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
Symmetrical Dense Optical Flow Estimation with Occlusions Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Two-Frame Optical Flow Formulation in an Unwarping Multiresolution Scheme
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Second order variational optic flow estimation
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
International Journal of Computer Vision
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One of the main technique used to recover motion analysis from two images or to register them is variational optical flow, where the pixels of one image are matched to the pixels of the second image by minimizing an energy functional. In the standard formulation of variational optical flow, the estimated motion vector field depends on the reference image and is asymmetric. However, in most application the solution should be independent of the reference image. Only few symmetrical formulations of the optical flow has been proposed in the literature, where the solution is constraint to be symmetric using a combination of the flow in both directions. We propose a new symmetric variational formulation of the optical flow problem, where the flow is naturally symmetric. Results on the Yosemite sequence show an improved accuracy of our symmetric flow with respect to standard optical flow algorithm.