Violent behavior monitoring method

Abstract

The invention discloses a violent behavior monitoring method comprising the steps that the image of a current video frame is acquired, and the binary foreground image of the image of the current video frame is extracted; the binary foreground image of the image of the current video frame is compared with a violent behavior template so as to obtain the similarity R; the global motion intensity E is calculated according to the image of the current video frame and the image of the previous video frame; fusion calculation of a violent behavior index is performed according to the similarity R and the global motion intensity E; and if the violent behavior index is greater than the preset threshold, the violent behavior occurs and the system transmits an alarm signal. The violent crime situation can be more accurately and timely discovered especially in the closed places so that the victims of the violent crime can be more timely rescued.

Description

technical field [0001] The invention relates to the field of security protection, in particular to the field of monitoring violence based on various scenarios. Background technique [0002] With the continuous development of the urbanization process, more and more airtight places similar to ATM machine operating rooms and elevator cars have appeared in cities. In recent years, violent crimes have occurred frequently in relatively closed places. And because of the airtightness of these places, it is difficult to detect these violent crimes when they occur, so that the victims cannot be helped in time. [0003] In cities, surveillance cameras are generally installed in the relatively closed places mentioned above. These monitoring systems are only responsible for recording and returning the events in the monitoring scene. In this way, after a major event occurs, evidence can be obtained after the event through video, disputes can be resolved, and the case can be cracked. H...

AI Technical Summary

Problems solved by technology

However, the existing monitoring system lacks effective data analysis functions, and cannot accurately and timely automatically discover abnormal events in the scene

[0004] In addition, in some more important places, the pictures captured by the surveillance cameras are sent back to the monitoring center, and the monitoring center often has to have monitoring personnel to monitor and analyze the real-time pictures

[0005] This will not only increase the cost of monitoring, but also a monitoring person often monitors multiple screens, which is likely to cause work fatigue, and the response is not timely and accurate, resulting in unsatisfactory monitoring accuracy and efficiency.

Images