A METHOD AND SYSTEM FOR ROBUST OBJECT TRACKING USING PARTICLE FILTER FRAMEWORK

摘要

A method and system for providing robust object tracking mechanism using a combination of a deterministic approach and a stochastic approach in a particle filter framework, is disclosed. The method includes computing object likelihood for consecutive frames using the state parameters of the tracked object within short time interval. The method performs a trend analysis of the tracking mechanism based on the computation of the object likelihood in the current frame and by determining the state drift values of an object likelihood function. Based on the calculation of the state drift values and the object likelihood function, sampling function variance is updated to correct the tracking mechanism.