571 search results - page 27 / 115 » Learning to Track with Multiple Observers |
SDM
2004
SIAM
13 years 9 months ago
2004
SIAM
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
ICMLA
2010
13 years 5 months ago
2010
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
ECCV
2010
Springer
14 years 22 days ago
2010
Springer
Maintaining the stability of tracks on multiple targets in video over extended time periods remains a challenging problem. A few methods which have recently shown encouraging resul...
CVPR
2010
IEEE
14 years 4 months ago
2010
IEEE
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
CVPR
2010
IEEE
14 years 4 months ago
2010
IEEE
We propose a novel tracking algorithm that can work robustly in a challenging scenario such that several kinds of appearance and motion changes of an object occur at the same time....