Abnormal Behavior Detection Method for Dense Passenger Flow

Abstract

The present invention provides a method for detecting abnormal behavior of dense passenger flow, which mainly extracts and analyzes the group movement features within the field of view of each camera in the sparse monitoring network, so as to separately judge the movement outside the field of view of each camera Behavior and the location where abnormal movement behavior may occur, and then determine the group movement behavior in the monitoring blind area formed by the area outside the field of view of each camera, and realize the analysis of group movement behavior in the monitoring field of view of the sparse monitoring network , to detect and judge the behavior of abnormal movement of groups outside the monitoring field of view, so that a small number of cameras can form a monitoring network that can cover a large area.

Description

technical field [0001] The invention relates to the technical field of video image information processing, in particular to a method for detecting abnormal behavior of dense passenger flow. Background technique [0002] In recent years, there have been many research results and practical applications of video surveillance technology in the direction of intelligence and networking. With the continuous improvement of public security needs, on the one hand, the behavior detection and analysis of only a few individuals can no longer meet the monitoring needs, and group movement analysis has attracted more and more attention. On the other hand, in order to realize the seamless monitoring of public places, it is necessary to deploy a large number of video monitoring points to expand the monitoring range. The ideal mode is to use multiple cameras to fully cover the monitoring area. These cameras overlap or are adjacent to each other in the field of view to obtain a continuous scen...

AI Technical Summary

Problems solved by technology

However, this will leave monitoring blind spots between different camera fields of view. Once abnormalities occur in these areas, managers will not be able to detect them in time and deal with them accordingly.

[0003] Therefore, it is necessary to propose a method for detecting abnormal behaviors of dense passenger flow, so as to effectively solve the problem that the monitoring blind spots in the sparse monitoring network cannot be detected in time and dealt with accordingly

Images