258 search results - page 3 / 52 » Multiple Object Tracking with Kernel Particle Filter |
CVPR
2005
IEEE
14 years 8 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...
HUMO
2007
Springer
13 years 8 months ago
2007
Springer
Tracking of rigid and articulated objects is usually addressed within a particle filter framework or by correspondence based gradient descent methods. We combine both methods, suc...
SIBGRAPI
2007
IEEE
14 years 1 months ago
2007
IEEE
This paper presents a new approach to multiple objects tracking that combines particle filters and k-means. The approach has been tested under an important real world situation, ...
TIP
2010
13 years 1 months ago
2010
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
ICIP
2005
IEEE
14 years 8 months ago
2005
IEEE
This paper presents a probabilistic framework for off-line multiple object tracking. At each timestep, a small set of deterministic candidates is generated which is guaranteed to ...