A method and system for robust object tracking using particle filter framework

摘要

A method and system are disclosed that provide a robust object tracking mechanism using a combination of deterministic and probabilistic approaches in a particle filter framework. The method includes calculating object likelihood for successive frames using the state parameter of the object being tracked within a short time. The method performs trend analysis of the tracking mechanism based on the calculation of the object likelihood and the determination of the state drift value of the object likelihood function in the current frame. To modify the tracking mechanism, the sampling function variance is updated based on the calculation of the state drift value and the object likelihood function.