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189
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ICCV
2003
IEEE
16 years 9 months ago
2003
IEEE
In recent years particle filters have become a tremendously popular tool to perform tracking for non-linear and/or non-Gaussian models. This is due to their simplicity, generality...
209
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ICCV
2001
IEEE
16 years 9 months ago
2001
IEEE
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
202
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ICCV
2001
IEEE
16 years 9 months ago
2001
IEEE
Many motion detection and tracking algorithms rely on the process of background subtraction, a technique which detects changes from a model of the background scene. We present a n...
200
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ICCV
2001
IEEE
16 years 9 months ago
2001
IEEE
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
212
click to vote
ICCV
2001
IEEE
16 years 9 months ago
2001
IEEE
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...