40 search results - page 1 / 8 » Kernel-Based Bayesian Filtering for Object Tracking |
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...
CVPR
2004
IEEE
14 years 6 months ago
2004
IEEE
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
ICCV
2007
IEEE
13 years 6 months ago
2007
IEEE
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
Although more efficient in computation compared to other tracking approaches such as particle filtering, the kernel-based tracking suffers from the "singularity" problem...
ICIP
2005
IEEE
14 years 6 months ago
2005
IEEE
Most object tracking approaches either assume that the number of objects is constant, or that information about object existence is provided by some external source. Here, we show...