Learning Higher-order Transition Models in Medium-scale Camera Networks

@article{Farrell2007LearningHT,
  title={Learning Higher-order Transition Models in Medium-scale Camera Networks},
  author={Ryan Farrell and David S. Doermann and Larry S. Davis},
  journal={2007 IEEE 11th International Conference on Computer Vision},
  year={2007},
  pages={1-8}
}
We present a Bayesian framework for learning higher- order transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the network and have a greater predictive power for multi-camera tracking than camera adjacency alone. These models also provide inherent resilience to camera failure, filling in gaps left by single or even multiple non-adjacent camera failures. Our approach to estimating higher-order transition models relies on the… CONTINUE READING
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