In order to solve the poor robustness problem due to using single feat ure in the target tracking process,a novel mean shift tracking algorithm based on adaptive multi-features fusion is presented in c omplex environment.In the process of the dynamic changes of the scene,several reliable features are selected according to their ability to distinguish target and background,by which the target model is represented,the multi-features model is established, and the feature importance weights are set.Mean shift target localization formula of multi-features fusion is proposed.By evaluatin g the reliability of the different features in different scenes dynamically,the feature weight is updated and the multiple features are fused ad aptively.According to the weights of different features,a selective template updating mechanism is put forward to alleviate the model drif ts.Experimental results indicate the robustness and effectiveness of the proposed method in complex scene.