A two-stage dynamic model, is a composition of two separate dynamic models: the liberal and conservative dynamic model. The liberal model explicitly modells the correlation in the target’s velocity by a nonzero-mean Gauss-Markov (GM) process and allows greater perturbation in the target’s velocity. The mean of the GM process is then estimated using a conservative estimate of the current target’s velocity. A particular composition of the two models allows using extremely low number of particles in the particle filter with improved performance in comparison the two widely-used dynamic models: the random walk and the nearly-constant velocity models.

An example of tracking a person from a moving camera is shown below. In this experiment we have used a, bootstrap particle filter, the color-based visual model which uses background to improve tracking and the two-stage dynamic model. The number of particles in the particle filter was set to only 25 particles.

We have analyzed the properties of the two-stage dynamic model in great detail on several examples of tracking and we have proposed practical directions for adjusting the model’s parameters for the particular application. These direction require only some general notion of target’s motion, such as how much pixels is the target expected to move in two consecutive images. For more details, see the papers below, and the accompanying homepage.

## Relevant Publications: