ATM self-service business hall behavior analysis method based on depth information

Abstract

The invention relates to an ATM self-service business hall behavior analysis method based on depth information. Behavior analysis based on common two-dimensional cameras is adopted in the prior art, and the situation that targets cannot be accurately positioned exists. According to the ATM self-service business hall behavior analysis method, firstly, binocular cameras are adopted for serving as acquisition equipment for the depth information, background modeling is carried out on depth maps, a Gaussian mixture model of each pixel is learned and updated, and background distribution is determined; secondly, the probability value of each pixel in each new depth map is worked out, and clustering segmentation is carried out on a front depth map according to the DENCLUE algorithm; finally, pixels in each human body region in each camera are projected onto the ground, association of projected targets is carried out by using multi-camera offset calibration, and therefore target detection under the multiple cameras is achieved under a global coordinate system. The depth information is used and background modeling of RGB information is combined, so that the stability of target detection is greatly improved, and a good basis is provided for following behavior analysis.

Description

technical field [0001] The invention belongs to the technical field of video intelligent monitoring, and relates to a behavior analysis method of an ATM self-service business hall based on depth information. Background technique [0002] At present, the technology based on video intelligent analysis has been gradually applied to the field of financial security, especially for ATM self-service business halls. Due to the frequent occurrence of robbery cases across the country, real-time early warning and active alarm based on video behavior analysis have become a strong technology in many areas. An important means of technological security. [0003] The video-based behavior analysis algorithm mainly provides detection functions such as "withdrawal trailing", "fighting", "smashing an ATM machine", "falling to the ground", "lingering", and "staying", but at this stage, these functions They are all realized based on the ordinary cameras originally installed by the bank. The beh...

AI Technical Summary

Problems solved by technology

The behavior analysis algorithm based on ordinary two-dimensional cameras is a research hotspot in the entire academic circle, but its maturity is not high. The main reason is that the target detection itself under the two-dimensional camera is immature. In this situation, behavioral analysis lacks a stable basis

[0004] Therefore, many banks that have applied behavior analysis products now report the problem of low algorithm detection rate or high false detection rate, and sometimes even affect the original security monitoring business of the bank.

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