Method and device for judging road traffic accidents

Abstract

The invention discloses a road traffic accident discrimination method and device. By acquiring a video image of a monitored road section; extracting lane lines from the video image; and performing multi-target detection and tracking on vehicles on each lane, the driving track of the vehicle is determined; According to the relative position of the vehicle's driving track and the lane line, it is judged whether the lane change phenomenon occurs in each vehicle. When the driving track of the vehicle deviates from the range of the current lane, it is determined that the lane changing phenomenon occurs; The coordinate difference of the feature points is used to judge whether each vehicle has a sudden stop. When the coordinate difference is lower than the preset threshold, it is determined that a sudden stop has occurred; when multiple vehicles in the same lane of the monitored road section are detected to change lanes When there is a sudden stop phenomenon and / or a sudden stop phenomenon, it is determined that a traffic accident has occurred on the monitored road section. The application improves the accuracy of accident discrimination, and can better adapt to various extreme car accident problems such as large deformation of the vehicle.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a method and device for judging road traffic accidents. Background technique [0002] The modern intelligent traffic video monitoring system has the ability to obtain rich information including lane congestion and vehicle violations more accurately and comprehensively, and can monitor various traffic conditions required by multiple lanes in real time. It has very good application and research value. [0003] For the identification of road traffic accidents, the current intelligent traffic video surveillance system mainly focuses on the feature extraction of the foreground targets of existing traffic events, and performs vehicle size segmentation for various types of vehicles including cars, buses and trucks. The traffic incidents are judged and identified by using the closed value of the area and the closed value of the width-to-length ratio of various vehicles in the de...

AI Technical Summary

Problems solved by technology

Due to the need to train multiple images and use a classifier for real-time classification in this existing traffic accident discrimination method, the information processing speed is slow, and it lacks universal application for special traffic events, such as large deformation of vehicles, etc. sex

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