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A video analysis-based real-time people flow monitoring method suitable for a dense scene

A real-time monitoring and video analysis technology, applied in the field of information processing, can solve the problems that cannot be solved in the actual scene of the airport, and achieve the effect of improving accuracy

Active Publication Date: 2019-06-21
THE SECOND RES INST OF CIVIL AVIATION ADMINISTRATION OF CHINA
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

like figure 1 As shown, passengers in the key areas of the airport are characterized by high-density, almost static, and severe occlusion scenes. This solution cannot solve the actual scene of the airport.

Method used

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  • A video analysis-based real-time people flow monitoring method suitable for a dense scene
  • A video analysis-based real-time people flow monitoring method suitable for a dense scene
  • A video analysis-based real-time people flow monitoring method suitable for a dense scene

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Experimental program
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Effect test

Embodiment 1

[0093] A method for real-time monitoring of crowd flow in dense scenes based on video analysis, see figure 2 , including the following steps:

[0094] S1: Foreground extraction that eliminates lighting effects, including:

[0095] S11: Connect to the airport security platform according to the H264 standard protocol, and extract a frame of background image every second.

[0096] S12: Use the mixed Gaussian model extracted every frame to perform background learning on the background image, for example, perform learning and extraction every 10 seconds, and learn 100 frames of images in total.

[0097] S13: Input the background image (set as B), the original image of the foreground (set as O), grayscale the background image B and the original image O of the foreground (set as H respectively B 、H O ); Calculate the normalized histogram of the background image B and the foreground original image O and calculate the average brightness (set as m B , m O ).

[0098] S14: Determi...

Embodiment 2

[0115] Embodiment 2 On the basis of Embodiment 1, combined with the collected images of the airport, the application of the present invention will be described in detail.

[0116] (1) Extract the foreground image.

[0117]Use the mixed Gaussian model to extract the background image B, and extract and learn every 10 frames of images;

[0118] Set the pixel value I of each pixel in the background image at time t t (x, y) is described by K (the value of K is 5) Gaussian models; then the probability P(I t (x, y)) is:

[0119]

[0120] Among them, x, y are the abscissa and ordinate of the pixel; i∈[1,2,...,K]; and are the weight, mean and variance of the i-th Gaussian model of the pixel point (x, y) at time t, respectively, and N represents the vector composed of the pixel value at time t, the mean and variance of the i-th Gaussian model.

[0121] After the mixed Gaussian background model of each pixel is established, it can be used to judge whether each pixel of the curr...

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Abstract

According to the video analysis-based real-time people flow monitoring method suitable for a dense scene. The method includes: acquiring a background image of a to-be-monitored area, and carrying outbackground learning on the background image by using a Gaussian mixture model; Obtaining a foreground original image of a to-be-monitored area, performing linear change on the background image and theforeground original image, and determining a change coefficient; Determining a threshold value by using the variation coefficient, and extracting a foreground image with a background removed from theforeground original image; Calculating the size of a pixel point occupied by a foreground individual in the foreground image by using a film and television perspective model; And determining the pedestrian flow of the to-be-monitored area by combining the shielding factor. The method is based on the existing video monitoring environment of the airport, and the passenger service quality is furtherimproved under the premise of improving the passenger travel experience and the target of reasonable service resource distribution.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a method for real-time monitoring of crowd flow in dense scenes based on video analysis. Background technique [0002] At present, the airport realizes the monitoring of the flow of people, mainly in the following categories: [0003] (1) Use sensing devices, such as bluetooth, wifi and other sensing devices to realize the overall passenger flow distribution in the terminal building and the queuing situation of passengers in the security check area. Due to the incomplete coverage of the sensing device in this method, the data collection granularity is relatively coarse, and the distribution of the crowd and the queuing situation of the crowd cannot be obtained finely. [0004] (2) Using the extraction, learning and matching of human head features, the counting of the number of people in the entrance and exit and passage is realized. This method adopts...

Claims

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Application Information

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IPC IPC(8): G06K9/00
Inventor 党婉丽罗谦耿龙邓睿王东华周杨
Owner THE SECOND RES INST OF CIVIL AVIATION ADMINISTRATION OF CHINA
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