Video monitoring system based on dynamic image detection

Abstract

The invention discloses a video monitoring system based on dynamic image detection. The video monitoring system comprises an image monitoring system and a dynamic image detection system, the dynamic image detection system comprises a second image collection module, a dynamic image processing module and a wireless transmission module, monitoring areas on front ends of the second image collection module and the image monitoring system are the same, and the clocks are synchronous; the dynamic image detection system receives a current image, performs dynamic image analysis on the current image and a previous frame of reference image, and transmits a dynamic image and a timestamp of the dynamic image to a background storage server and / or a remote monitoring terminal via the wireless transmission module through the Internet; and the background storage server marks the stored video monitoring information by using the dynamic image and the timestamp of the dynamic image and preferentially covers the unmarked video monitoring information during circular storage. Compared with the prior art, the video monitoring system has the advantages that the dynamic image detection system accesses the original image monitoring system in a wireless manner, therefore the hardware architecture of the original image monitoring system does not need to be changed.

Description

technical field [0001] The invention belongs to the field of video monitoring, in particular to a video monitoring system based on dynamic image detection. Background technique [0002] At present, most of the widely used image monitoring systems in the market adopt static image monitoring, regardless of whether there are moving objects in the monitoring area, they are all collected and stored, which requires a large amount of storage space for the system and increases the cost of the system. In order to reduce storage costs, the existing technology usually adopts a circular storage method, that is, the latest video is used to overwrite the older content, but since the earlier video is overwritten, the information contained in it will be lost, and the general monitoring system has a minimum Requirements for effective storage time. With the maturity of high-definition camera technology, high-definition cameras are used more and more widely. The cameras in traditional monitor...

AI Technical Summary

Problems solved by technology

[0002] Most of the image monitoring systems widely used in the market currently use static image monitoring, regardless of whether there are moving objects in the monitoring area, they are collected and stored, which requires a large amount of storage space for the system and increases the cost of the system

In order to reduce storage costs, the existing technology usually adopts a circular storage method, that is, the latest video is used to overwrite the older content, but since the earlier video is overwritten, the information contained in it will be lost, and the general monitoring system has a minimum Effective Storage Time Requirements

With the maturity of high-definition camera technology, high-definition cameras are used more and more widely. The cameras in traditional monitoring systems have been upgraded to high-definition cameras. According to the existing storage technology, the storage space required is getting larger and larger, resulting in the original monitoring system. After upgrading the camera, the effective storage time cannot meet the storage requirements of the user, resulting in the need to upgrade the entire system, resulting in a waste of resources and an increase in cost

In practice, in some applications, such as schools, factories, office buildings, etc., few people appear at night, but the camera is working as usual. The video recorded in this way may have no effect at all. takes up storage space

[0003] At the same time, the static image monitoring adopted in the prior art cannot give early warning of emergencies, and the monitoring video can only be viewed manually in real time or afterwards. Loss

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