Infrared Object Tracking Algorithm Based on Covariance Matrix and Auxiliary Particle Filter

To improve the capability of capturing object rotation for traditional region covariance matrix,improved infrared object tracking algorithm using elliptical region covariance matrix and auxiliary particle filter is proposed. Firstly,through extending the rectangle covariance region,the ellptical covariance matrix descriptor is constructed. Meanwile,the improved lie group structure 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 auxiliary particle filter. Experiment results verify the effectives and robustness of the proposed algorithm which can improve the tracking performance efficiently.