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FGR
2004
IEEE
185views Biometrics» more  FGR 2004»
13 years 9 months ago
Real Time Hand Tracking by Combining Particle Filtering and Mean Shift
Particle filter and mean shift are two successful approaches taken in the pursuit of robust tracking. Both of them have their respective strengths and weaknesses. In this paper, w...
Caifeng Shan, Yucheng Wei, Tieniu Tan, Fréd...
ECCV
2000
Springer
14 years 7 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, ...
CVPR
2008
IEEE
14 years 7 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
FGR
2008
IEEE
192views Biometrics» more  FGR 2008»
13 years 6 months ago
Tracking a walking person using activity-guided annealed particle filtering
Tracking human pose using observations from less than three cameras is a challenging task due to ambiguity in the available image evidence. This work presents a method for trackin...
John Darby, Baihua Li, Nicholas Costen
ICIAP
2005
ACM
14 years 5 months ago
Scatter Search Particle Filter for 2D Real-Time Hands and Face Tracking
This paper presents the scatter search particle filter (SSPF) algorithm and its application to real-time hands and face tracking. SSPF combines sequential Monte Carlo (particle fil...
Antonio S. Montemayor, Juan José Pantrigo, ...