The interest point based tracking methods suffer from the limitation of unavailability of sufficient number of matching key points for the target in all frames of a running video. In this paper, a dynamic model is proposed for describing the object model which is used for tracking a human in a non-stationary video. This dynamic model takes into account the change in the pose as well as the motion of the human. A simple autoregression based predictor is used for dealing with the case of full occlusion. Simulation results are provided to show the efficacy of the algorithm. © 2013 IEEE.
|Name||2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings|
|Conference|| 2013 IEEE International Conference on Image Processing|
|Period||15/09/13 → 19/09/13|
- Auto-regression prediction
- Human Tracking