Method, device, system and storage medium for determining target objects in public transport

Abstract

The present invention relates to a method and system for determining a target object in a public transportation vehicle. The method includes: after a new event occurs, acquiring face images of people entering and leaving the public transportation vehicle where the incident occurred during the time period / station period when the new event occurs as the waiting time Comparing data; counting past event data that occurred in public transportation vehicles, determining the identification of high-frequency public transportation vehicles with frequent incidents, and the high-frequency time periods and high-frequency stations of each high-frequency public transportation vehicle with different identifications Obtain the face image of entering and leaving the high-frequency public transport with the first identification in the high-frequency time period and high-frequency site as historical data; compare the data to be compared with the historical data, according to The comparison result selects the target object from the personnel corresponding to the data to be compared. The present invention determines the historical data available for collision through the statistical analysis of the historical incident data, and collides the data of the time period and site segment when the new event occurs with the historical data, so that the target object can be quickly determined, and the meet the needs of practical applications.

Description

technical field [0001] The invention belongs to the technical field of monitoring, and in particular relates to a method, device, system and storage medium for determining a target object in a public vehicle. Background technique [0002] At present, under the vigorous promotion of "Safe City" and "Snow Bright Project", a large number of security surveillance cameras or bayonet cameras have been installed in the city, which has greatly reduced the crimes of two robbery and one robbery on the streets of the city, but for There is still no effective control method based on cases in public transportation. For example, if a mobile phone is lost in a bus, when the victim finds it, the time and place of discovery may not be consistent with the time and place of loss. For subsequent cases The detection has caused a lot of trouble, and cases such as thefts in the public transport space have not been effectively detected. The current detection methods are in trouble, mainly for the ...

AI Technical Summary

Problems solved by technology

[0003] 1. You can’t see the behavior of all the people in the public transportation, and you can only determine the people who get on and get off the car. When a case occurs, it is impossible to determine which one is suspected;

[0004] 2. In cases of theft in public transportation, there will be a certain period of time between the theft and the discovery of the victim, so that people who do not know when to get on and off the bus may be suspected;

[0005] 3. According to statistics, most of the cases are carried out by former criminals, so it is expected to determine the target by colliding the data of the current theft case with the data of the past theft cases. However, when colliding with the past data, the past data The amount is huge, and I don’t know which period of time data will collide with it

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