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A real-time monitoring threat analysis method and system based on deep learning

A technology for threat analysis and real-time monitoring, applied in neural learning methods, transmission systems, closed-circuit television systems, etc. The effect of pressure, reducing labor cost and improving security efficiency

Active Publication Date: 2021-08-06
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is: the present invention provides a real-time monitoring threat analysis method and system based on deep learning, which solves the problem of poor real-time performance and accuracy caused by the large amount of monitoring data in the existing monitoring system and the large workload of monitoring staff. The problem of low efficiency has achieved the effect of reducing the pressure on security personnel to manually analyze monitoring data, reducing labor costs and improving security efficiency

Method used

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  • A real-time monitoring threat analysis method and system based on deep learning
  • A real-time monitoring threat analysis method and system based on deep learning
  • A real-time monitoring threat analysis method and system based on deep learning

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Embodiment 1

[0039] A real-time monitoring threat analysis method based on deep learning, comprising the following steps:

[0040] Step 1: the video acquisition unit collects video information;

[0041] Step 2: The video analysis and processing unit sequentially performs image preprocessing based on the neural network, target detection based on the grid extraction layer, and threat analysis based on the deep neural network to obtain analysis results and send them to the video cloud processing server;

[0042] Step 2 includes the following steps:

[0043] Step 2.1: The image preprocessing module in the video analysis and processing unit sequentially decodes, decomposes, down-samples and normalizes the video information to obtain several frames of monitoring image data;

[0044] Step 2.2: The target detection module in the video analysis processing unit monitors the image data for each frame based on the neural network using structural layers such as the convolutional layer and the grid ext...

Embodiment 2

[0057] First, the video acquisition unit performs image acquisition on the monitoring area, and the acquisition device adopts a high-definition surveillance camera or a camera on a wearable device or a camera of a mobile phone.

[0058] The image data collected by the video acquisition unit is encoded by the video encoder and then transmitted to the video cloud processing server through a wireless network or an optical fiber cable network. The video cloud processing server stores the obtained data in the video cloud processing server before processing the data. backup, and then send the data to the video analysis and processing unit for processing.

[0059] The video analysis and processing unit preprocesses the monitoring video data.

[0060] The preprocessing steps are:

[0061] S101: Decoding the surveillance video, and then decomposing the video into images frame by frame;

[0062] S102: Downsampling each frame of image to change the image to a resolution of 448*448, so ...

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Abstract

The invention discloses a real-time monitoring threat analysis method and system based on deep learning, and relates to the field of intelligent monitoring based on deep learning; the method comprises the following steps: 1) a video acquisition unit collects video information; 2) a video analysis and processing unit sequentially performs Image preprocessing based on neural network, target detection based on grid extraction layer and threat analysis based on deep neural network get the analysis results and send them to the video cloud processing server; 3) The video cloud processing server transmits the analysis results to the video display The unit performs output to complete real-time monitoring and threat analysis; the invention solves the problems of poor real-time performance and accuracy caused by the large amount of monitoring data in the existing monitoring system, and the low efficiency caused by the heavy workload of monitoring staff, and achieves the reduction of labor for security personnel. Analyze the pressure of monitoring data, reduce labor costs and improve security efficiency.

Description

technical field [0001] The invention relates to the field of intelligent monitoring based on deep learning, in particular to a real-time monitoring threat analysis method and system based on deep learning. Background technique [0002] Convolutional neural network is a deep learning model that can automatically extract features and perform sampling. It has high use value in the field of image processing; it has the characteristics of fast running speed, good adaptability, efficient extraction of image features and translation invariance. , suitable for image processing. [0003] In modern society, video surveillance system plays a very important role in the field of security; nowadays, surveillance cameras can be seen everywhere. According to statistics, there are more than 200 million surveillance cameras in the world, which does not include all kinds of cameras that can be converted to surveillance at any time. Devices, such as mobile phones, notebooks, smart glasses, etc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/08G06Q50/26H04L29/08H04N7/18
CPCH04N7/18G06N3/084G06Q50/265G06V40/10G06V40/20G06V20/41G06V20/52G06V10/56H04L67/56G06F18/2148G06F18/24
Inventor 高建彬甘卓欣
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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