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CVPR
2004
IEEE
16 years 5 days ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black
TIP
2002
183views more  TIP 2002»
14 years 9 months ago
Speckle reducing anisotropic diffusion
This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sens...
Yongjian Yu, Scott T. Acton
85
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ICIP
2010
IEEE
14 years 8 months ago
Joint color decrosstalk and demosaicking for CFA cameras
In interest of low cost, low power consumption, and compact size, most digital cameras adopt a design of single sensor array coupled with a color filter array. This design inevita...
Xiaolin Wu, Xiangjun Zhang
ICIP
2007
IEEE
15 years 12 months ago
Isomap Tracking with Particle Filtering
The problem of tracking involves challenges like in-plane and out-of-plane rotations, scaling, variations in ambient light and occlusions. In this paper we look at the problem of ...
Nikhil Rane, Stanley T. Birchfield
CVPR
2003
IEEE
16 years 5 days ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...