Target tracking method and device, computer equipment and storage medium

Abstract

The invention relates to the field of image processing in artificial intelligence, and discloses a target tracking method and device, computer equipment and a storage medium. The method comprises thesteps that a real-time mechanical arm state and an image sequence containing a target object are acquired according to a preset sampling period; the real-time mechanical arm state and the image sequence containing the target object are input into a target object tracking model, and motion parameters output by the target object tracking model are obtained, wherein the target object tracking model is a prediction model constructed based on a DDPG algorithm; and the motion state of the mechanical arm is controlled according to the motion parameters to enable the mechanical arm to move following the target object. The target tracking method and device can reduce the development cost of the target tracking, improve the training efficiency of the target tracking model, and can be applied to theconstruction of the smart city. At the same time, the target tracking method and device also relates to a blockchain technology.

Description

technical field [0001] The invention relates to the field of image processing in artificial intelligence, in particular to a target tracking method, device, computer equipment and storage medium. Background technique [0002] At present, object tracking methods have been widely used in video surveillance, industrial manufacturing, smart home, smart photography and other fields. The target tracking method includes image target detection and motion control. First, use image target detection to detect single-frame or multi-frame images, determine the target position, then calculate motion parameters (such as velocity vector, acceleration vector) according to the target position, and control the robot arm to follow the target according to the motion parameters. However, both of these two parts require a lot of tedious labeling, training and tuning work to ensure the accuracy of target tracking. These labeling, training and tuning tasks require manual participation, which great...

AI Technical Summary

Problems solved by technology

However, both parts require a lot of tedious labeling, training and tuning work to ensure the accuracy of target tracking

These labeling, training and tuning tasks require manual participation, which greatly increases the development cost of the target tracking method, and the training efficiency is not high

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