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ICIP
2003
IEEE
14 years 9 months ago
An optical flow probabilistic observation model for tracking
In this paper, we define an observation model based on optical flow information to track objects using particle filter algorithms. Although the optical flow information enables us...
Antonio Garrido Carrillo, José M. Fuertes, ...
IBPRIA
2003
Springer
14 years 24 days ago
Probabilistic Observation Models for Tracking Based on Optical Flow
In this paper, we present two new observation models based on optical flow information to track objects using particle filter algorithms. Although optical flow information enabl...
Manuel J. Lucena, José M. Fuertes, Nicolas ...
ICCV
2011
IEEE
12 years 11 months ago
Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling
Human motion capturing (HMC) from multiview image sequences constitutes an extremely difficult problem due to depth and orientation ambiguities and the high dimensionality of the s...
Gerard Pons-Moll, Andreas Baak, Juergen Gall, Laur...
FGR
2008
IEEE
170views Biometrics» more  FGR 2008»
14 years 2 months ago
Using an adaptive VAR Model for motion prediction in 3D hand tracking
A robust VAR-based (vector autoregressive) model is introduced for motion prediction in 3D hand tracking. This dynamic VAR motion model is learned in an online manner. The kinemat...
Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph
ICIP
2002
IEEE
14 years 17 days ago
Segmentation-based object tracking using image warping and Kalman filtering
We propose a segmentation-based method of object tracking using image warping and Kalman filtering. The object region is defined to include a group of patches, which are obtained ...
Yu Huang, Thomas S. Huang, Heinrich Niemann