Abstract
Smoking in driving not only reduces the accuracy of driving operation, but also leads to insufficient oxygen and higher possibility of traffic accident. Therefore, considering the safety of life and avoiding accidents as far as possible, a detection model based on deep learning which can quickly detect smoking driving behavior is designed. In this model, convolutional neural network is used to process the input frames of the video stream captured by the camera. After the shape feature extraction, fuzzy feature processing, motion feature detection and color feature region comparison, the smoking driving behavior can be judged. Through the design of a series of computer vision detection modules, not only can reduce the calculation of the model, but also improve the efficiency of deduction, so as to meet the performance requirements of real-time monitoring. In order to quickly find out the driver smoking behavior and trigger warning, so as to avoid unnecessary traffic accidents and ensure life safety.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call