As an effective visual target tracking algorithm

the tracking-learning-detection(TLD) has drawn wide attention around the world. In this paper

we propose an improved TLD visual target tracking algorithm

which is obtained by making several improvements based on the original TLD algorithm. The improvements include modifying local tracker placement as well as local tracker failure predicting method for the tracker of TLD to improve the precision and robustness of the tracker; employing Kalman filter in the detector of TLD for estimating the location of the target to reduce the scanning region of the detector and improve the speed of the detector; adding Markov model based target moving direction predictor in the detector of TLD to increase the discretion for targets with similar appearance. Experiments have been conducted to compare the performance of the original TLD and improved TLD. The experimental results show that

compared with the original TLD

the improved TLD has more accurate tracking precision

faster tracking speed and stronger distinguishing ability for targets with similar appearance in the scene.