Information tracking method based on convolutional neural network

The invention provides an information tracking method based on a convolutional neural network. The method comprises the following steps: constructing a correlation filtering convolutional neural network in combination with correlation filtering and a convolutional neural network; constructing a time flow convolutional neural network and a spatial flow convolutional neural network on the basis; the three parts are constructed to form a deep network in a jumping connection mode; training the deep network until the three models are all converged; respectively extracting image block feature information in the current frame and a motion change feature information set of a target between frames in a plurality of time sequences through a time stream convolutional neural network and a spatial stream convolutional neural network; fusing the image block feature information and the motion change feature information weight, constructing a full-connection neural network, and obtaining prediction information of the current frame target; and fusing all models by using a Bagging algorithm to determine final prediction information of the current frame, constructing a time network and a space network on the basis of a related filtering network, further capturing time information and space information of a target, and improving the accuracy of the algorithm.