Camera monitoring alarm method and device

Abstract

The invention discloses a camera monitoring alarm method and device. The method and device are used for monitoring the positions and movement conditions of a camera in real time and can send out alarm information in time when the camera moves. The method includes the steps that movement indexes which represent movement changes of the monitored camera are collected in real time; the movement indexes are compared with a preset corresponding alarm threshold value; the corresponding alarm information is output according to the comparison result that the movement indexes exceed the alarm threshold value.

Description

technical field [0001] The invention relates to the technical field of monitoring and alarming, in particular to a camera monitoring and alarming method and device. Background technique [0002] In today's daily life, there are basically situations where cameras are used to monitor scenes, such as traffic probes, community probes, and so on. In the process of using the camera to monitor, the camera has the function of shooting the monitoring scene. Generally, it will be fixed or reciprocating to patrol the set area. If it is artificially damaged, such as knocking, etc., it will cause the camera body to move abnormally. In addition to human factors, the long-term outdoor environment may also cause damage to the bracket, which indirectly leads to abnormal shifting of the camera. These situations will cause abnormal changes in the monitoring area of ​​the shifted camera, and the preset monitoring cannot be achieved. Purpose. [0003] The existing monitoring of camera position...

AI Technical Summary

Problems solved by technology

[0004] This image intelligence algorithm has the problems of low recognition rate and high false alarm rate in the following scenarios:

[0005] 1. The brightness of the monitored scene is low, such as night and dark places;

[0006] 2. When the video content changes greatly (the monitored scene has many moving objects and a large amount of movement), etc.;

[0007] 3. Large changes in light and shadow, weather effects

[0008] In these scenarios, the accuracy rate of recognition through intelligent recognition is low, and there are a large number of false alarms, so it is impossible to accurately determine the abnormality of the camera

Moreover, there is often a delay in the use of image intelligence algorithms. In the monitoring system, it is impossible to feed back abnormal information in time for a large number of cameras.

[0009] In summary, under the existing technology, managers cannot accurately and timely grasp the working status of the camera

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