Statistical method of number of people in monitoring video

Abstract

The invention relates to a statistical method of a number of people in a monitoring video. The method comprises the following steps of establishing a pedestrian sample database; for each frame of video image, using a hybrid Gaussian background modeling method and combining morphological filtering so as to acquire a foreground image; through calculating a number of foreground pixels in the foreground image, acquiring a foreground area and a normalization scene area; taking image foreground as a template, extracting Harris angle point information and SURF characteristic point information, and using an effective characteristic point number in an unit area to represent a shielding degree among groups in a scene; taking a normalization scene area S2 and crowd shielding factors D1 and D2 as an input vector and taking a statistical people number in the scene as an output vector, and training a BP network to complete construction of a regression model T1; extracting an HOG characteristic in the pedestrian sample database and using an Adaboost cascade classifier T2 to train a corresponding pedestrian detector; and constructing a combination classifier and realizing adaptive calculating of a weight during classifier fusion.

Description

technical field [0001] The invention belongs to the field of intelligent video monitoring. Specifically, it is a real-time people counting system based on computer vision. Background technique [0002] In recent years, with the improvement of people's attention to security and the development of modern security technology, video surveillance systems have been widely used in all aspects of social life, from the security of banks and exhibition halls to the monitoring of squares and campuses. , From the working environment to the family environment, the video surveillance system plays an irreplaceable role in social public security and punishing crimes, safeguarding the prosperity and stability of the society, and promoting the development and construction of a harmonious society. [0003] However, traditional video surveillance systems have their own limitations. First of all, its functions are relatively simple. It only has simple monitoring video storage and playback func...

AI Technical Summary

Problems solved by technology

[0003] However, traditional video surveillance systems have their own limitations

First of all, its functions are relatively simple. It only has simple monitoring video storage and playback functions. Its main function is forensic analysis after the event. However, the real-time analysis ability of the monitored scene is relatively lacking, and it does not have the function of providing real-time early warning for abnormal events that occur.

Secondly, in order to achieve the purpose of real-time monitoring, the monitoring room of the unit or department that has installed the monitoring camera needs security personnel to monitor without interruption around the clock, which is a great waste of human and material resources.

At the same time, security personnel are prone to fatigue when working continuously for a long time, so the probability of missed judgments and misjudgments will greatly increase

It can be seen that if we simply rely on traditional manpower for monitoring, we cannot adapt to the current development trend.

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