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» Denoising image sequences does not require motion estimation
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EMMCVPR
2011
Springer
12 years 8 months ago
Optical Flow Guided TV-L1 Video Interpolation and Restoration
The ability to generate intermediate frames between two given images in a video sequence is an essential task for video restoration and video post-processing. In addition, restorat...
Manuel Werlberger, Thomas Pock, Markus Unger, Hors...
ICIP
1997
IEEE
14 years 10 months ago
Model-Based Estimation of Facial Expression Parameters from Image Sequences
In this paper we present a model-based algorithm for the estimation of 3D motion and the analysis of facial expressions of a speaking person. A set of facial animation parameters ...
Peter Eisert, Bernd Girod
VCIP
2001
199views Communications» more  VCIP 2001»
13 years 10 months ago
Estimation of large-amplitude motion and disparity fields: application to intermediate view reconstruction
This paper describes a method for establishing dense correspondence between two images in a video sequence (motion) or in a stereo pair (disparity) in case of large displacements....
Moustapha Kardouchi, Janusz Konrad, Carlos V&aacut...
ICIAP
2003
ACM
14 years 8 months ago
Dense 3D interpretation of image sequences: a variational approach using anisotropic diffusion
The purpose of this study is to investigate a new method for recovering relative depth and 3D motion from a temporal sequence of monocular images. The method is direct insomuch as...
Hicham Sekkati, Amar Mitiche
CIMAGING
2010
133views Hardware» more  CIMAGING 2010»
13 years 10 months ago
Motion blur removal in nonlinear sensors
We address the problem of motion blur removal from an image sequence that was acquired by a sensor with nonlinear response. Motion blur removal in purely linear settings has been ...
Tomer Faktor, Tomer Michaeli, Yonina C. Eldar