Logistic regression-based queuing anomaly detection method and device

Abstract

The invention relates to a logistic regression-based queuing anomaly detection method and device. The device comprises a hard disk video recorder module and a format conversion module; the hard disk video recorder module is a device for storing monitoring videos; monitoring videos collected by a business hall are stored in the hard disk video recorder; when queuing detection is performed on different windows or counters in the business hall, the video information of corresponding windows or counters is required to be read from the hard disk video recorder; when the video information is read, user names and passwords are required to be provided; the format conversion module performs format conversion on the videos; the format of the videos stored in the hard disk video recorder is a YUV format; and since the queuing detection is realized based on opencv, the YUV format is required to be converted into a format which is recognizable for the opencv. The logistic regression-based queuing anomaly detection method and device of the invention are superior to traditional head recognition means and can assist in solving the problem of poor universality. According to the method and device of the invention, a large number of head samples are adopted to perform training; an obtained classifier is utilized to recognize heads; and therefore, recognition accuracy can be improved, and interference is little.

Description

technical field [0001] The invention relates to a queuing abnormality detection method and device based on logistic regression. Background technique [0002] With the advent of the information age, there are more and more applications of intelligent video surveillance, and the research on video queuing detection is becoming more and more extensive. The traditional head detection based on contour or shape mainly extracts the head characteristics according to the characteristics of the head Outline, the purpose of counting people is achieved by calculating the outline. This method is relatively simple to implement, but the interference is large, and the recognition accuracy is not high. [0003] The traditional contour-based head detection method first extracts the black area, extracts the outline of the black area, and then performs shape analysis. It is judged as a head if it is close to the shape of the head. However, the shape of the head is not clearly defined, and after ...

AI Technical Summary

Problems solved by technology

[0002] With the advent of the information age, there are more and more applications of intelligent video surveillance, and the research on video queuing detection is becoming more and more extensive. The traditional head detection based on contour or shape mainly extracts the head characteristics according to the characteristics of the head Contour, by calculating the contour to achieve the purpose of people counting, this method is relatively simple to implement, but the interference is large, and the recognition accuracy is not high

[0003] The traditional contour-based head detection method first extracts the black area, extracts the outline of the black area, and then performs shape analysis. It is judged as a head if it is close to the shape of the head. However, the shape of the head is not clearly defined, and after using binarization processing The head area may be divided into blocks, which also affects the recognition accuracy

This detection method is not very versatile for the black area extraction method that is difficult to use when wearing a hat or bald head

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