Focusing on the problem of object tracking

an object-tracking algorithm based on visual saliency and particle filtering is proposed. Based on the research results of the human visual attention mechanism

this algorithm integrates features such as color

intensity and motion to generate the visual saliency feature. Both

the visual saliency feature and the color distribution model

are used as the representation model of the object. Particle filtering is used to track the object. This algorithm can overcome the instability brought by using a single color feature. It can also solve the difficulty caught by object shape changes

illumination variation

and the problems caused by target objects and background having similar color distributions. The algorithm has been tested on many video sequences. Experiment results and analysis are presented in this paper. The experimental results show that this algorithm is robust and it is effective and valid for object tracking.