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Method for warning traffic accidents in real time on basis of videos

A traffic accident and video technology, which is applied in traffic flow detection, instruments, character and pattern recognition, etc., can solve the problems that the results are easily affected by the subjective influence of observers, have poor reliability, and cannot meet the application requirements, and achieve high accuracy , reliable early warning, and easy-to-achieve effects

Active Publication Date: 2015-06-24
CHINA HIGHWAY ENG CONSULTING GRP CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The existing real-time early warning method of traffic accidents is mainly manual observation, that is, the driver observes and judges the traffic information on the road on the spot to realize traffic early warning, but the result is easily affected by the subjective influence of the observers, the reliability is poor, and it cannot meet the application requirements

Method used

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  • Method for warning traffic accidents in real time on basis of videos
  • Method for warning traffic accidents in real time on basis of videos
  • Method for warning traffic accidents in real time on basis of videos

Examples

Experimental program
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Effect test

Embodiment 1

[0057] In the video sequence, two vehicles are selected and numbered, the former vehicle is recorded as the second vehicle, and the latter vehicle is recorded as the first vehicle. From the 10th frame image to the 30th frame image, a stable trajectory line is obtained by detecting and tracking the first vehicle, and a stable trajectory line is obtained by detecting and tracking the second vehicle. In the 30th frame, a corner point on the first vehicle is selected as the target position of the first vehicle by screening, and a corner point on the second vehicle is selected as the target position of the second vehicle. According to the mapping table, S1=983 meters, S2=1003 meters, and the actual distance between the two vehicles is 20 meters. In the 10th frame, select a corner point on the first vehicle as the target position of the first vehicle through screening, select a corner point on the second vehicle as the target position of the second vehicle, and obtain S3=959 meters ...

Embodiment 2

[0059] In the video sequence, two vehicles are selected and numbered, the former vehicle is recorded as the second vehicle, and the latter vehicle is recorded as the first vehicle. From the 10th frame image to the 30th frame image, a stable trajectory line is obtained by detecting and tracking the first vehicle, and a stable trajectory line is obtained by detecting and tracking the second vehicle. In the 30th frame, a corner point on the first vehicle is selected as the target position of the first vehicle by screening, and a corner point on the second vehicle is selected as the target position of the second vehicle. Get S according to the mapping table 1 = 900 meters, S 2 =940 meters, the actual distance between the two vehicles is 40 meters. In the tenth frame, a corner point on the first vehicle is selected as the target position of the first vehicle through screening, and a corner point on the second vehicle is selected as the target position of the second vehicle. Get ...

Embodiment 3

[0061] In the video sequence, two vehicles are selected and numbered, the former vehicle is recorded as the second vehicle, and the latter vehicle is recorded as the first vehicle. From the 10th frame image to the 20th frame image, a stable trajectory line is obtained by detecting and tracking the first vehicle, and a stable trajectory line is obtained by detecting and tracking the second vehicle. In the 20th frame, a corner point on the first vehicle is selected as the target position of the first vehicle by screening, and a corner point on the second vehicle is selected as the target position of the second vehicle. Get S according to the mapping table 1 = 750 meters, S 2 =800 meters, the actual distance between the two vehicles is 50 meters. In the 10th frame, a corner point on the first vehicle is selected as the target position of the first vehicle through screening, and a corner point on the second vehicle is selected as the target position of the second vehicle. Accord...

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Abstract

The invention relates to a method for warning traffic accidents in real time on the basis of videos. The method includes starting to continuously track n images from an optional N image to obtain a movement track of a first vehicle and a movement track of a second vehicle; acquiring angular points and recording positions of the two angular points of the two vehicles in the images; acquiring particular positions of the angular points according to a mapping table; acquiring actual running speeds of the vehicles; and computing the safety time between the two vehicles to determine a safety level so as to warn a traffic accident in real time. Compared with the prior art, the method for warning the traffic accidents in real time on the basis of the videos has the advantages that the method can be implemented without environmental constraints, all vehicles within a video range can be reliably warned in real time, and the method is easy to implement, is high in accuracy, is quite suitable for real-time traffic warning and has a broad application prospect.

Description

technical field [0001] The invention belongs to the field of video detection, in particular to a video-based real-time early warning method for traffic accidents. Background technique [0002] Recently, casualties, traffic jams, environmental pollution, and economic losses caused by traffic accidents are increasing rapidly with the increase of traveling vehicles. Therefore, the research on fast and effective real-time early warning of traffic accidents has attracted more and more attention. The video-based real-time early warning method for traffic accidents improves the real-time monitoring of moving vehicles and the rapid response to abnormal traffic conditions, while effectively reducing road maintenance costs. In addition, because it reduces a lot of tedious work, it can be greatly improved. Reduce the consumption of manpower and material resources, reduce costs, improve work efficiency and the operation level of the entire road network. At present, the real-time early...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06K9/00
Inventor 王国锋彭玲玲席阳宋焕生李建成李东方张鹏宋鹏飞
Owner CHINA HIGHWAY ENG CONSULTING GRP CO LTD
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