Target tracking method based on bounding box regression model

Abstract

The invention discloses a target tracking method based on bounding box regression, which mainly solves the problem of inaccuracy of a target area predicted by a traditional correlation filter. The method comprises the steps of calculating a spatial feature map with continuous resolution; calculating a correlation filter; constructing a bounding box regression model; returning to the predicted target position; taking the adjusted target area position as a target tracking result; judging whether the current frame of video image is the last frame of image of the to-be-tracked video image sequenceor not, if so, executing the next step, and otherwise, executing from the beginning by using the next frame; and ending the tracking of the to-be-tracked target. According to the method, by constructing the bounding box regression line, the position information of the target area is more accurately predicted, the characteristics of the neural network extracted from the target area are enriched ina cubic linear interpolation mode, and finally, accurate target tracking is realized.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a target tracking method based on a bounding box regression model in the technical field of computer vision image processing. The invention adopts a method based on the combination of bounding box regression and self-adaptive model, and realizes the tracking of moving objects in the fields of video monitoring, medical care, intelligent transportation, robot navigation, human-computer interaction, virtual reality and the like. Background technique [0002] The main task of target tracking is to estimate the trajectory of the target in the video, that is, to detect the moving target to be tracked from the video image sequence, and then determine the position of the moving target in each frame of image. One of the most popular methods for object tracking is detection tracking, which is usually based on a discriminative learning model, where a binary classifier is lear...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the above-mentioned deficiencies in the prior art, and propose a target tracking method based on bounding box regression, which is used to solve the problem that the process of re-detection by the tracker after tracking failure is time-consuming, and the obtained target area not accurate enough

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