Abstract: Robust tracking of non-rigid objects is a challenging task. Particle filter is a powerful tool for vision tracking based on sequential Monte Carlo framework and proved very successful for non-linear and non-Gaussian estimation problem. This paper proposes a tracking algorithm based on particle filter and optimized Likelihood. Colour distributions are applied as they are robust to partial occlusion, rotation, scale invariant and computationally efficient. As the colour of an object can vary over time dependent on the illumination, the