Infrared Object Tracking Algorithm Based on Extended Spatial Histogram

To improve the low discriminative ability of object model with only color information in traditional mean shift algorithm, improved mean shift tracking algorithm using spatio and gray features is proposed.Firstly, through extending the spatio histogram, the joint spatio-gray object model is constructed with both gray distribution and spatio relationship.Meanwile, the joint probability density function is defined to build the similarity measure between the object model and candidate model.Finally, the accurate localization of infrared object is realized by the extended mean shift algorithm.Experiment results verify the effectives and robustness of the proposed algorithm which can improve the tracking performance efficiently.