ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
Particle filters have been introduced as a powerful tool to estimate the posterior density of nonlinear systems. These filters are also capable of processing data online as requir...
ECCV
2006
Springer
14 years 7 months ago
2006
Springer
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
ECCV
2008
Springer
14 years 7 months ago
2008
Springer
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
ICCV
2001
IEEE
14 years 7 months ago
2001
IEEE
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
ICCV
2003
IEEE
14 years 7 months ago
2003
IEEE
In recent years particle filters have become a tremendously popular tool to perform tracking for non-linear and/or non-Gaussian models. This is due to their simplicity, generality...
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
Particle filters encode a time-evolving probability density by maintaining a random sample from it. Level sets represent closed curves as zero crossings of functions of two variab...
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. ...
ICCV
2009
IEEE
14 years 10 months ago
2009
IEEE
We propose a novel framework for contour based object
detection and recognition, which we formulate as a joint
contour fragment grouping and labeling problem. For a
given set of...