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CVPR
2004
IEEE
16 years 8 months 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»
15 years 6 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
ICIP
2010
IEEE
15 years 4 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
16 years 8 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 8 months 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...