Abnormal traffic condition detection method based on vehicle motion vector field analysis

Abstract

The invention provides an abnormal traffic condition detection method based on vehicle motion vector field analysis. The abnormal traffic condition detection method based on the vehicle motion vector field analysis comprises using a frame-to-frame difference method based on blocks to detect a motion area, finding out feature points of the motion area, obtaining travel tracks of vehicles in motion, recording travel tracks of all the vehicle in motion, forming a vehicle motion vector field, and comparing the vehicle motion vector field with a vehicle motion vector field in a video by combing a normal vehicle motion vector field to confirm whether the travel tracks of the vehicles are normal. The abnormal traffic condition detection method based on the vehicle motion vector field analysis avoids limitation of a complicated background environment, is capable of carrying out real-time and reliable detection on all the vehicles in motion in a video range, and is easy to achieve, high in accuracy, and wide in application respect.

Description

technical field [0001] The invention belongs to the field of video detection, in particular to a method for detecting abnormal traffic conditions based on vehicle motion vector field analysis. Background technique [0002] Numerous traffic accidents take place every year, one of the reasons why traffic accidents occur frequently when driving illegally. Therefore, using video surveillance to quickly and accurately detect traffic incidents has become a concern of more and more people. The goal of the intelligent video surveillance system is to monitor and understand the events that are happening in the scene, and to alarm the abnormal events according to the preset requirements; predict the upcoming events according to the state or position of the moving target, and reduce the dangerous events happened. The first is to be able to learn in real time, recognize the behavior trajectory patterns of normal moving objects, and detect abnormal moving object trajectories on this bas...

AI Technical Summary

Problems solved by technology

These methods are simple in principle, clear in physical concepts, and easy to implement, but there are also defects such as complex hardware systems, poor environmental adaptability, high failure rates, and inconvenient maintenance, which are difficult to promote in actual use.

Video-based methods include background difference method to extract moving vehicles, but in complex environments, background extraction and update have always been a difficult problem, which also greatly affects the quality of extracted moving objects

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