DDGNet-YOLO: A Target Detection Network For Dangerous Driving Gestures
Yefan Zhou, Zhao Lv, Yongtai Zhou · 2020
As we all know, some bad driving behaviors such as using mobile phone, eating, drinking etc., may lead to traffic accidents. In order to reduce these potential dangers, we proposed a target detection network to detect the abovementioned dangerous driving gestures. We have improved the YOLOv4 target detection network and designed the DDGNet- YOLO target detection network, so as to reduce the detection time of dangerous driving gesture. Our algorithm have been performed on the CVRR-HANDS 3D dataset. The [email protected] of dangerous driving gesture is 76.4%, and the average real-time processing speed of the algorithm was 143 frames per second.