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» Learning to Track with Multiple Observers
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ICPR
2006
IEEE
14 years 8 months ago
Multiple Object Tracking Using Local PCA
Tracking multiple interacting objects represents a challenging area in computer vision. The tracking problem in general can be formulated as the task of recovering the spatio-temp...
Bernhard Frühstück, Csaba Beleznai, Hors...
ECCV
2010
Springer
13 years 10 months ago
Probabilistic Deformable Surface Tracking From Multiple Videos
Abstract. In this paper, we address the problem of tracking the temporal evolution of arbitrary shapes observed in multi-camera setups. This is motivated by the ever growing number...
CVPR
2005
IEEE
14 years 9 months ago
Multiple Collaborative Kernel Tracking
Those motion parameters that cannot be recovered from image measurements are unobservable in the visual dynamic system. This paper studies this important issue of singularity in th...
Zhimin Fan, Ying Wu, Ming Yang
CVPR
2010
IEEE
14 years 3 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox