A suspect early warning method and system based on face recognition

A face recognition and early warning system technology, applied to the suspect early warning method and system field based on face recognition, can solve the problems of low efficiency, inaction in work, unclear bus activities of suspects, etc. Achieve the effect of saving data resources, precision features, and fast speed

Inactive Publication Date: 2019-01-15
成都智达万应科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] (1) The suspect appears in a public area such as a bus, but the system cannot give an early warning in real time, and does not proceed to deal with it;
[0007] (2) You can only search for video to find evidence after the event, and cannot directly provide relevant picture information during the incident;
[0008] (3) The activities of the suspect on the bus are unclear;
[0009] (4) Security video image data, the traditional processing method is mainly completed by manual inspection after the event, and the efficiency is extremely low

Method used

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  • A suspect early warning method and system based on face recognition
  • A suspect early warning method and system based on face recognition
  • A suspect early warning method and system based on face recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0069] Such as figure 1 As shown, a suspect early warning method based on face recognition includes the following steps:

[0070] a. Extract the face image of the suspect, and calculate the feature value of the face image of the suspect;

[0071] b. Compare and analyze the feature value of the suspect's face image with the feature value of the face image in the blacklist database filed by the Public Security Bureau;

[0072] C, judge whether this suspect's facial image feature value is recorded in the blacklist database of public security bureau filing, if yes, then send alarm signal to driver, enter step d; If not, then enter step b again;

[0073] d. The dispatch monitoring center automatically receives the alarm signal, retrieves the monitoring video, and sends the alarm information to the Public Security Bureau.

[0074] In this embodiment, when a person boards the vehicle, the face image of the person boarding the vehicle is collected through the infrared high-definitio...

Embodiment 2

[0076] This embodiment is on the basis of embodiment 1, as figure 2 As shown, the step a includes the following steps:

[0077] a101. Establish training sample image set There are C categories of images, each category n i of which, X k Indicates the kth training sample image, N is the total number of training sample images;

[0078] a102. Define the inter-class dispersion matrix Intra-class dispersion matrix and the generalized Fisher criterion function J F (W)=W T SB W / W T S W W; where, and respectively represent the mean value of the i-th class training sample image and the mean value of the total training sample image, T is the transpose, and W is the best projection direction;

[0079] a103, according to the mean value of the i-th class training sample image calculated and the mean of the total training sample images Calculate the inter-class scatter matrix and intra-class scatter matrix of the training sample image set;

[0080] a104, take The orth...

Embodiment 3

[0086] On the basis of embodiment 2, this embodiment also includes the following steps:

[0087] According to the distributed cache memcache technology, the obtained feature value of the suspect's face image is called into the memory, and when it needs to be called, it is read from the memory. Using the distributed cache memcache technology, the face recognition technology has the characteristics of fast speed and high precision; and it ensures high-performance access to data. When there is no more space in the memory to store new data, memcache will Use the LRU (Least Recently Used) algorithm to eliminate recently infrequently accessed data to make room for new data and save data resources.

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PUM

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Abstract

The invention discloses a suspect early warning method based on face recognition. The suspect face image eigenvalue is calculated by extracting the suspect face image. The eigenvalues of suspects' face images are compared with those in the blacklist database filed by the public security bureau. Judging whether the characteristic value of the suspect's face image is recorded in the blacklist database filed by the public security bureau, if so, sending an alarm signal to the driver, uploading the alarm signal to the dispatching monitoring center, and sending the alarm information to the public security bureau; if not, the eigenvalue comparison analysis is performed again. The invention also discloses a suspect early warning system based on face recognition, comprising a face image extractionmodule, an eigenvalue comparison module, a suspect judgment module and a monitoring alarm module. The invention realizes high-precision and high-efficiency face recognition, facilitates the identification of suspect basic information, understands suspect personnel activity, and can real-time call monitoring video, on-line video-on-demand, saving bandwidth resources.

Description

technical field [0001] The invention relates to the technical field of monitoring, in particular to a suspect early warning method based on face recognition and a system thereof. Background technique [0002] With the rapid development of my country's economy and society, buses play an irreplaceable role in people's travel methods, and the quality and safety of buses are constantly improving. Therefore, more and more people choose to take buses. Airports and high-speed railways now have strict monitoring and authentication systems, and buses may become used by suspects such as thieves and fugitives, and may endanger the safety of passengers on board after getting on the bus. Buses cover a large area throughout the city and become an important part of a smart city. Passenger safety needs to be improved, which is equally important to the safety of airports and high-speed rail. For security video image data, the traditional processing method mainly relies on manual inspection ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06Q50/26
CPCG06Q50/26G06V40/166G06V40/168G06V40/172
Inventor 王博严俊
Owner 成都智达万应科技有限公司
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