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CVPR
2003
IEEE
14 years 9 months ago
Nonparametric Belief Propagation
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
ICIP
2001
IEEE
14 years 9 months ago
Tracking of human activities using shape-encoded particle propagation
We present an approach to tracking human activities in a monocular video. We model the human body by decomposing it into torso and limbs and use simple 3D shapes to approximate th...
Hankyu Moon, Rama Chellappa, Azriel Rosenfeld
ICASSP
2011
IEEE
12 years 11 months ago
Optimal SIR algorithm vs. fully adapted auxiliary particle filter: A matter of conditional independence
Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse the Sampling Importanc...
François Desbouvries, Yohan Petetin, Emmanu...
ECCV
2006
Springer
14 years 9 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
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...
Charles Florin, Nikos Paragios, James Williams
ICIP
2005
IEEE
14 years 9 months ago
Shape space sampling distributions and their impact on visual tracking
Object motions can be represented as a sequence of shape deformations and translations which can be interpretated as a sequence of points in N-dimensional shape space. These space...
Amit Kale, Christopher O. Jaynes