Abstract: In order to reduce the execution time of visual image target tracking and improve the accuracy of tracking track, a visual image target tracking method based on improved convolutional neural network algorithm is proposed. In order to obtain shorter target tracking execution time and better target tracking track, video image processing technology is used to extract the foreground of visual image, improved convolutional neural network algorithm is used to extract the features of visual image, MeanShift target tracking algorithm is used to track visual image targets on the basis of visual image features. And the tracking results of MeanShift target tracking algorithm are further optimized through Kalman filtering, realizing visual image target tracking. Experimental results show that the proposed method has short execution time and high tracking accuracy.

Key words: convolutional neural network, visual image, target tracking, Kalman filter