The invention discloses a visual target tracking method based on deep residual network characteristics. The visual target tracking method comprises the following steps: 1, selecting a characteristic layer of a deep residual network and calculating a weight; 2, extracting features of the first frame of actual input image; 3, constructing a response and initial position filter of the characteristicsof the first frame of actual input image; 4, performing scale sampling and fHOG feature extraction on the first frame of actual input image; 5, constructing an initial scale filter; 6, feature extraction of the second frame of actual input image; 7, position filtering; 8, weighting a position filtering response graph and positioning a target; 9, performing scale sampling and fHOG feature extraction on the target image; 10, performing scale filtering and scale estimation on the target feature vector; 11, updating the filter; And 12, inputting a next frame of actual input image, regarding the next frame of actual input image as a second frame of actual input image, and repeating the step 6. The method is high in tracking precision and success rate, adapts to target scale changes, and achieves the robust tracking of the target.