54 search results - page 3 / 11 » Distributed Gaussian particle filtering using likelihood con... |
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
In this paper, we present a novel method for model estimation for visual servoing. This method employs a particle filter algorithm to estimate the depth of the image features onli...
CVPR
2003
IEEE
14 years 7 months ago
2003
IEEE
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
CVPR
2004
IEEE
14 years 7 months ago
2004
IEEE
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...
IROS
2009
IEEE
13 years 12 months ago
2009
IEEE
Abstract— Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) a...
CDC
2009
IEEE
13 years 10 months ago
2009
IEEE
— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...