KCF target tracking method employing CNN in integrated manner

Abstract

The invention discloses a KCF (Kernel Correlation Filtering) target tracking method employing CNN (Convolution Neural Network) in integrated manner and belongs to the technical field of image processing. First, a first frame of a video is read, characteristics of a target is extracted and idealization output is given at the same time; a KCF template is obtained through training. Then, a next frameof image is read, a tracking result of a KCF algorithm is calculated and a KCF response map and a target result KCF_Box are obtained; and a PSR value of the KCF algorithm is calculated. Whether the PSR value is greater than an algorithm threshold value or not is judged. If the PSR value is greater than an algorithm threshold value, calculation employing a GOTURN algorithm is not needed and KCF_Box as the result of the KCF algorithm is taken as the tracking result of the current frame. If the PSR value is not greater than an algorithm threshold value, calculation employing the GOTURN algorithmis performed and a tracking result GOTURN_Box of the GOTURN algorithm is taken as the tracking result of the current frame. Finally, template update of the KCF algorithm and network input update of the GOTURN algorithm are performed. According to the invention, a side lobe ratio is taken as a bridge and an integration method for the KCF algorithm and the GOTURN algorithm is proposed, so that theaccuracy of the target tracking result is ensured.

Description

technical field [0001] The invention belongs to the technical field of image processing, and more specifically relates to a kernel correlation filtering target tracking method fused with a convolutional neural network. Background technique [0002] Computer vision is an important part of the computer field. It is a subject that studies how to make computers have human vision functions. It uses computers to simulate human vision, and uses computer technology to process, analyze and understand images of external objects. As an important research content in the field of computer vision, object tracking technology has received extensive attention and research from scholars at home and abroad in recent years. Target tracking is a comprehensive technology that uses video sensors to locate and track specific targets by analyzing and understanding video information. [0003] Target tracking technology integrates the knowledge of image processing, mathematics and physics, and has a ...

AI Technical Summary

Problems solved by technology

[0005] The tracking algorithm based on correlation filtering regards the tracking process as a process of template matching and ridge regression. This method transforms the convolution in the time domain into the point product in the frequency domain by performing Fourier transform on the dense candidate samples. , which greatly saves the amount of calculation, so this algorithm can often obtain a higher running speed, but this method will cause poor tracking effect when the template is occluded or deformed;

[0006] The tracking algorithm based on convolutional neural network (CNN) has good tracking ability for complete targets in simple scenes, and is robust to scale changes and deformations, but the algorithm is not effective for overly complex scenes.

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