Variable Kernel Bandwidth Tracking Algorithm Based on Contourlet Histogram and Information Entropy

Abstract

In order to solve the problem that traditional mean shift tracking algorithm based on color histogram is easily affected by similar color non-target object and the change of the size of target, a variable kernel bandwidth tracking algorithm is put forward based on contourlet histogram and information entropy. The target is modeled by contourlet histogram, as iterative parameters in mean shift algorithm, and according to the relationship between information entropy and the size of target, a scale-update item is added to mean shift algorithm to track the target that has a change in size. Experimental results show that the proposed tracking algorithm can not only effectively overcome the interference of similar color non-target object in the scene, but also adapt to the changes in target’s size stably, and this algorithm had a good robustness.