Target tracking and intrusion detection method and device and storage medium

Abstract

The invention discloses a target tracking and intrusion detection method and device and a storage medium. The target tracking method comprises the following steps: acquiring a plurality of targets andinformation of each target in a current image frame based on a CNN detection algorithm, and acquiring a foreground image of the current image frame based on a motion detection algorithm; based on theforeground image, obtaining a moving object of which the confidence is less than a preset first threshold value from the plurality of objects; carrying out first information matching on the moving object with the confidence coefficient smaller than a preset first threshold value and the moving object pool updated by the previous image frame to obtain a first object, wherein the first object is the moving object with the confidence coefficient smaller than the preset first threshold value and successfully matched with the first information; and finally, obtaining a target trajectory of the current image frame based on a multi-target tracking algorithm and a second target of the current image frame, wherein the second target comprises the first target and a target of which the confidence isgreater than or equal to a preset first threshold in the current image frame. By means of the mode, the target detection rate is increased, and missing detection is reduced.

Description

technical field [0001] The present application relates to the technical field of security monitoring, in particular to a target tracking and intrusion detection method, device, and storage medium. Background technique [0002] Existing video surveillance technology is essentially human monitoring and semi-human monitoring. The semi-human monitoring method uses simple intelligent algorithms to identify a large number of abnormal behaviors, artificially filters false alarms, and classifies alarm targets. [0003] The existing intelligent monitoring algorithms mainly include two types: one is to use machine learning methods to identify intrusion behavior through motion detection and track the target's motion trajectory; the other is to use CNN detection to detect the target of the entire screen, and form trajectory to identify intrusion behavior. However, these existing technologies still have the problems of high labor cost and many false negatives. Therefore, a new method of...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved in this application is to provide a target tracking and intrusion detection method, device, and storage medium to solve the problems of high labor cost and many missed and false positives in the prior art

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