Target Tracking Method Based on Correlation Filter and Particle Filter

Abstract

Object tracking is one of the most important tasks in computer vision, many researchers have proposed a lot of effective methods to solve the all kinds of the recent problems in object tracking. During the movement of the targets, the change of object scale may produce a lot of difficulties in object tracing problems, and it may lead to be failed in tracking. The paper proposed method is designed both correlation filter and particle filter. In order to achieve the purpose of tracking, the process of correlation filter is to learn an array of filters so that the response value obtained by the convolution of the learned filters is the largest. The particle filter guides the sample particles to the distribution mode of the target state. The samples of the particle strategy can effectively deal with the large scale variations of the target during movement. Experiment on the OTB database shows that the paper proposed method makes good performance.