Research on vehicle collision detection method based on computer vision
In order to quickly identify road vehicle collision accidents,a vehicle collision detection method based on machine vision is proposed.This method uses the YOLOv5 deep neural model to achieve rapid recognition of vehicles;On this basis,Kalman filtering and Hungarian matching algorithm are introduced to achieve multi target tracking of vehicles;Using the visual odometry calculation method,parameters such as vehicle speed,overlap,and trajectory deflection are obtained,and the occurrence of a collision is judged by whether the above parameters are abnormal.The test results show that compared with existing algorithms,this method has a significant improvement in recognition accuracy.
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