Traffic Light Recognition and Dangerous Driving Events Detection from Surveillance Video of Vehicle Camera
Color and shape of traffic lights are different in different countries and areas. Color and shape of traffic light images are also different at different shooting time, background and weather condition. It is difficult for conventional method to obtain both high recognition rate and low false positive rate. We proposed to use color, shape and context features to recognize traffic light more accurately.
Vehicle road testing in both USA and Japan were made to demonstrate effectiveness of our proposed method. Real-time processing recognition experiments were made by vehicle camera video stream. Surveillance videos taken by driving recorder camera were also used to do traffic light recognition and dangerous driving events detection experiments. Traffic light recognition rate of 93%, false positive detection rate of 0.1%, realtime processing time less than 30ms results were obtained by our method.
Keywords: DANGEROUS DRIVING EVENT DETECTION; RED LIGHT IGNORED; ROCKET START; SPEED AND ACCELERATION OF CAR; SURVEILLANCE VIDEO OF VEHICLE CAMERA; TRAFFIC LIGHT COLOR RECOGNITION; TRAFFIC LIGHT RECOGNITION; TRAFFIC LIGHT SHAPE RECOGNITION
Document Type: Research Article
Publication date: January 29, 2017
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