The Spatio-Temporal Context (STC) target tracking algorithm is based on the Bayesian framework and uses the spatio-temporal relationship between the tracked target and its surroundings to achieve the purpose of target tracking.However, it is easy to lose the tracked target when the target is rapidly moving or violently interfered.Therefore, in this paper, the STC target tracking algorithm is combined with Kalman filtering, the position of the target is predicted by using Kalman filter, and the prediction result is corrected by using the STC target tracking algorithm.The target tracking algorithm combining Kalman filtering and STC can realize effective target tracking when the target is occluded or when there is interference targets.The experimental results demonstrate that the accuracy and robustness of the proposed target tracking algorithm are better than that of the original STC target tracking algorithm.