258 search results - page 3 / 52 » Multiple Object Tracking with Kernel Particle Filter |
CVPR
2005
IEEE
14 years 7 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 7 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 20 hour 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 14 days 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 7 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 ...