Tracking Algorithm Based on Joint Features

Abstract

In the study of target tracking process, when the target has a similar color to the background easily leads to the loss of the target due to illumination and noise. In order to avoid the drawback of Mean shift which only uses color information as the features to track the target, Sobel operator and local binary patterns (LBP) are combined to extract the textures of the moving target as Mean shift characteristics. An advantage of the Mean shift algorithm can compute the histogram easily. However, this process can’t change the size of a search window. Therefore, the proposed method extracts the feature points of the object in the region that given by the improved Mean shift and according to the information that the positions of the special feature points, a new search window is generated. The experiments show that the proposed object tracking system performs more accurately than the Mean shift algorithm.