EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow
Résumé
We propose a novel approach for optical flow estima-tion, targeted at large displacements with significant oc-clusions. It consists of two steps: i) dense matching by edge-preserving interpolation from a sparse set of matches; ii) variational energy minimization initialized with the dense matches. The sparse-to-dense interpolation relies on an appropriate choice of the distance, namely an edge-aware geodesic distance. This distance is tailored to han-dle occlusions and motion boundaries, two common and difficult issues for optical flow computation. We also pro-pose an approximation scheme for the geodesic distance to allow fast computation without loss of performance. Sub-sequent to the dense interpolation step, standard one-level variational energy minimization is carried out on the dense matches to obtain the final flow estimation. The proposed approach, called Edge-Preserving Interpolation of Corre-spondences (EpicFlow) is fast and robust to large displace-ments. It significantly outperforms the state of the art on MPI-Sintel and performs on par on KITTI and Middlebury.
Fichier principal
epicflow.pdf (1.35 Mo)
Télécharger le fichier
contour_boundaries_temple_3_31.jpg (23.99 Ko)
Télécharger le fichier
Origine | Fichiers produits par l'(les) auteur(s) |
---|
Format | Figure, Image |
---|---|
Origine | Fichiers produits par l'(les) auteur(s) |