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Title:
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Motion inpainting by an image-based geodesic AMLE method
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Author:
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Oliver, Maria; Raad, Lara; Ballester, Coloma; Haro Ortega, Gloria
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Abstract:
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Comunicació presentada al congrés 25th IEEE International Conference on Image Processing (ICIP) celebrat del 7 al 10 d'octubre de 2018 a Atenes, Grècia. |
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Abstract:
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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). |
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Abstract:
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This work is partially supported by MINECO/FEDER UE project, with reference TIN2015-70410-C2-1-R and by RISE project NoMADS. |
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Subject(s):
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-Optical flow inpainting
-Sparse to dense methods
-Partial differential equations
-Absolute Minimal Lipschitz Extension
-Anisotropic methods |
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Rights:
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© 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/8451851
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Document type:
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Conference Object
Article - Accepted version |
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Published by:
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Institute of Electrical and Electronics Engineers (IEEE)
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