CONDENSATION - Conditional Density Propagation for Visual Tracking.

The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimo dal, cannot represent simultaneous alternative hypotheses. The C ondensation algorithm uses factored sampling, previously applied to the interpretation of static images, in which the probability distribution of possible interpretations is represented by a randomly generated set. C ondensation uses learned dynamical models, together with visual observations, to propagate the random set over time. The result is highly robust tracking of agile motion. Notwithstanding the use of stochastic methods, the algorithm runs in near real-time.