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ICCV
1999
IEEE
14 years 9 months ago
Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
Étienne Mémin, Patrick Pérez
CVPR
2011
IEEE
13 years 4 months ago
Camera Calibration with Lens Distortion from Low-rank Textures
We present a simple, accurate, and flexible method to calibrate intrinsic parameters of a camera together with (possibly significant) lens distortion. This new method can work u...
Zhengdong Zhang, Yasuyuki Matsushita, Yi Ma
P2P
2010
IEEE
207views Communications» more  P2P 2010»
13 years 6 months ago
Local Access to Sparse and Large Global Information in P2P Networks: A Case for Compressive Sensing
—In this paper we face the following problem: how to provide each peer local access to the full information (not just a summary) that is distributed over all edges of an overlay ...
Rossano Gaeta, Marco Grangetto, Matteo Sereno
CORR
2010
Springer
172views Education» more  CORR 2010»
13 years 7 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang
ECCV
2010
Springer
14 years 25 days ago
Compressive Acquisition of Dynamic Scenes
Abstract. Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Ny...