Target tracking method based on conditional adversarial generative twinning network

Abstract

The invention discloses a target tracking method based on a conditional adversarial generation twinning network. The method comprises the following steps: (1) acquiring real-time video data for data preprocessing; (2) inputting the data preprocessed in the step (1) into a conditional adversarial generation twin tracking network consisting of a conditional adversarial generation deblurring network module and a full-convolution twin tracking network; and (3) embedding the conditional adversarial generation deblurring network module subjected to adversarial optimization into the full-convolution twinning tracking network framework subjected to feedback updating, and performing target tracking on the preprocessed real-time video data by using a conditional adversarial generation twinning tracking network subjected to online combination to obtain a target position. The dynamic adjustment capability of the tracking network is enhanced, the robustness of a tracker is improved, the tracking network is subjected to separation training in a transfer learning mode, the over-fitting phenomenon is prevented, the training time is shortened, and the generalization capability of the tracking network is improved.

Description

technical field [0001] The present invention relates to the technical field of machine vision and target tracking, and more specifically relates to a target tracking method based on conditional confrontation generative twin network. Background technique [0002] Target tracking is one of the important research topics in the field of computer vision. Its main task is to obtain the position information of the target of interest in the video sequence, to realize the analysis and understanding of the behavior of the moving target, and to provide further semantic analysis (action recognition, scene, etc.) recognition, etc.) to provide the basis for completing more advanced tasks. As a middle-level and high-level processing stage in the field of computer vision, target tracking is an important technical means for intelligent analysis of video content. Through high-dimensional feature extraction and spatial coordinate positioning of the target of interest in the video frame sequenc...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the technical problem that the model drifts due to motion blur and low resolution when the tracked target is moving rapidly and violently, resulting in poor tracking effect or even tracking failure of the tracker

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