11 search results - page 1 / 3 » Classification-Based Likelihood Functions for Bayesian Track... |
AVSS
2006
IEEE
13 years 8 months ago
2006
IEEE
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
CVPR
2000
IEEE
13 years 8 months ago
2000
IEEE
This paper addresses the derivation of likelihood functions and confidence bounds for problems involving overdetermined linear systems with noise in all measurements, often referr...
ICCV
2005
IEEE
14 years 6 months ago
2005
IEEE
Classic methods for Bayesian inference effectively constrain search to lie within regions of significant probability of the temporal prior. This is efficient with an accurate dyna...
ICCV
2001
IEEE
14 years 6 months ago
2001
IEEE
Blob trackers have become increasingly powerful in recent years largely due to the adoption of statistical appearance models which allow effective background subtraction and robus...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...