An unmanned aerial vehicle visual target tracking method based on scale adaptive kernel correlation filtering

Abstract

The invention discloses an unmanned aerial vehicle visual target tracking method based on scale self-adaptive kernel correlation filtering, which comprises the following steps of selecting a trackingtarget, calculating to obtain the color and gradient initial probability density of a first frame of the tracking target, and training a classifier and detecting the central position of the target byusing the kernel correlation filtering algorithm for the first frame of data; establishing a one-dimensional kernel correlation filter from the second frame to detect the change of the target scale, and calculating kernel correlation filtering by using a convolution theorem; constructing a similarity function by utilizing the current target feature and the initial feature, if the similarity is smaller than a set threshold value, considering that the target identification is inaccurate or the target is lost, entering global search, otherwise, representing that the target is identified and tracked, and obtaining target position information; and sending the position information of the tracking target to an unmanned aerial vehicle flight control system in real time to control the position of the unmanned aerial vehicle. According to the method, the problem of fixed tracking scale of a kernel correlation filtering algorithm is optimized, and the tracking precision of target characteristicsis effectively improved.

Description

technical field [0001] The invention relates to the fields of UAV target tracking and computer vision, in particular to a UAV visual target tracking method based on scale adaptive kernel correlation filtering. Background technique [0002] In recent years, with the rapid development of UAV technology and computer vision technology, vision-based UAV aerial photography has been widely used, especially in the fields of investigation and surveillance, disaster search and rescue, and aerial photography. The multi-axis drone is an unmanned aerial vehicle with simple structure, vertical take-off and landing, and fixed-point hovering. It is composed of forward and reverse pairs of propellers symmetrically distributed on the body. The control of six degrees of freedom is generally driven by lithium batteries. [0003] However, most multi-axis UAVs currently on the market have a low degree of intelligence and automation, and cannot liberate the hands of the operator, which limits the...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the deficiencies in the prior art, the present invention provides a UAV visual target tracking method based on scale-adaptive kernel correlation filtering, which solves the current unmanned The UAV target tracking algorithm is relatively complex and takes a long time to run, which cannot meet the needs of UAV tracking

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