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» 3D Tracking by Catadioptric Vision Based on Particle Filters
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ICPR
2008
IEEE
14 years 8 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
CRV
2009
IEEE
217views Robotics» more  CRV 2009»
14 years 2 months ago
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...
ICPR
2008
IEEE
14 years 8 months ago
Spatio-temporal 3D pose estimation and tracking of human body parts using the Shape Flow algorithm
In this contribution we introduce the Shape Flow algorithm (SF), a novel method for spatio-temporal 3D pose estimation of a 3D parametric curve. The SF is integrated into a tracki...
Markus Hahn, Lars Krüger, Christian Wöhl...
ICPR
2008
IEEE
14 years 1 months ago
Behaviour based particle filtering for human articulated motion tracking
John Darby, Baihua Li, Nicholas Paul Costen
ECCV
2000
Springer
14 years 9 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...