Oliver, MariaRaad, LaraBallester, ColomaHaro Ortega, Gloria2018-11-222018-11-222018Oliver M, Raad L, Ballester C, Haro G. Motion inpainting by an image-based geodesic AMLE method. In: 2018 25th IEEE International Conference on Image Processing (ICIP); 2018 Oct 7-10; Athens, Greece. Piscataway (NJ): IEEE; 2018. p. 2267-71. DOI: 10.1109/ICIP.2018.84518512381-8549http://hdl.handle.net/10230/35820Comunicació presentada al congrés 25th IEEE International Conference on Image Processing (ICIP) celebrat del 7 al 10 d'octubre de 2018 a Atenes, Grècia.This work presents an automatic method for optical flow inpainting. Given a video, each frame domain is endowed with a Riemannian metric based on the video pixel values. The missing optical flow is recovered by solving the Absolutely Minimizing Lipschitz Extension (AMLE) partial differential equation on the Riemannian manifold. An efficient numerical algorithm is proposed using eikonal operators for nonlinear elliptic partial differential equations on a finite graph. The choice of the metric is discussed and the method is applied to optical flow inpainting and sparse-to-dense optical flow estimation, achieving top-tier performance in terms of End-Point-Error (EPE).application/pdfeng© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at https://ieeexplore.ieee.org/document/8451851info:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ICIP.2018.8451851Optical flow inpaintingSparse to dense methodsPartial differential equationsAbsolute Minimal Lipschitz ExtensionAnisotropic methodsinfo:eu-repo/semantics/openAccess