Long-time visual target tracking method based on continuous learning

The invention relates to a long-time visual target tracking method based on continuous learning. The method comprises the steps of network model design, model initialization, online tracking and modelupdating. A deep neural network structure is designed for long-time visual target tracking, an initialized network model is obtained through model initialization, then online tracking is conducted through the initialized network model, long-time or short-time model updating is conducted through a continuous learning method in the tracking process, and the method adapts to various changes of a target in the tracking process. According to the method, a traditional visual target tracking model online updating process is converted into a continuous learning process, and the complete appearance description of the target is integrally established from all historical data of the video, so that the robustness of long-term visual tracking is effectively improved. The method provided by the invention can provide an effective solution for long-term visual target tracking for application requirements of intelligent video monitoring, man-machine interaction, visual navigation and the like.