Smart community abnormality alarm system and method based on target track analysis

Abstract

The invention discloses a smart community abnormality alarm system based on target track analysis. The system comprises a person recognition module which recognizes a figure target from images uploaded by all image collection equipment in a community, a track point generation module which acquires the position of the identified figure target to generate track points of the figure target, a movingtrack generation module which sorts the track points of the same figure target according to a recognition time to generate a moving track of the figure target, and a moving track comparison module which compares the moving track of the figure target with a pre-established non-abnormal track template and judging whether a person belongs to an abnormal target or not according to a comparison result,and alarm information is sent to a security monitoring terminal if the moving track comparison module judges that the person belongs to the abnormal target. According to the system and the method, asuspicious person can be identified by judging the moving track comparison template of the same person such that security personnel can pay attention to the suspicious person, and measures can be taken when necessary to prevent damage to residents and property.

Description

technical field [0001] This application relates to the field of community public security and anti-theft technology, in particular to an abnormal alarm system in a smart community based on target trajectory analysis, and an abnormal alarm system in a smart community based on target trajectory analysis. Background technique [0002] For the community, public security and anti-theft is an important factor to avoid property loss of residents and maintain the safety and stability of people's daily life, especially for smart communities. Since the smart community is a community that provides intelligent services in buildings, homes, digital life, etc. by means of communication methods such as the Internet and the Internet of Things, so as to provide residents in the community with a safe, comfortable and convenient modern and intelligent living environment. Community security requirements will also be higher. [0003] At present, security monitoring is generally used to monitor ...

AI Technical Summary

Problems solved by technology

[0004] However, using the above-mentioned manual on-duty method to watch the surveillance video in real time and make a judgment on whether it is a suspicious person requires a high labor cost, and when there are many surveillance points with surveillance cameras, it is difficult to ensure that only relying on manpower Personnel screening in all monitoring areas, especially during the peak hours of resident travel, when the personnel on duty observe and distinguish the people in each monitoring area with the naked eye, they may not be able to ensure that suspicious people mixed in the crowd can be found in time, and they may not notice that they appear in the crowd. Suspicious people in uninhabited areas may cause thieves to burglary residents, which is not conducive to community security and stability

[0005] There are other ways to maintain the stability of the public security environment in the community, such as controlling patrol robots to replace manual patrols, but the cost of patrol robots is much higher than the cost of a large number of surveillance cameras, and it is inconvenient for robots to move within the floor. In addition, because patrol robots Due to its strong mobility, it is impossible to monitor a certain area 24 hours a day, and there are time gaps for thieves to successfully carry out theft, and it is impossible to reliably identify suspicious persons

Images