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» Denoising image sequences does not require motion estimation
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EMMCVPR
2011
Springer
13 years 11 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
16 years 1 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»
15 years 1 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
15 years 11 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»
15 years 1 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