Single target tracking method based on residual regression network

• Main Authors: ZHANG YONGDONG, WANG RUIHAI, ZHANG JIYONG, YANG HONGNAN, SUN YAOQI, YAN CHENGGANG
• Format: Patent
• Language: Chinese; English
• Published: 25.10.2019
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The invention discloses a single target tracking method based on a residual regression network. The method comprises the following steps: 1, preprocessing original training data; 2, inputting the preprocessed data into a residual regression network model, carrying out parameter training, and determining network parameters; 3, after the network parameters are determined, preprocessing the video sequence to be tracked according to the same mode as the step 1; and step 4, inputting a preprocessing result of the video sequence to be tracked into the residual regression network model to obtain a tracking result. The present invention increases speed and allows real-time tracking of objects. Compared with the prior art, the method provided by the invention has the advantages of effectively solving the problems of gradient dispersion and network precision, effectively restraining the problem of precision reduction, reducing the training difficulty of a deep network, greatly improving the precision of single-target t