Design and Implementation for an Automotive DMS system
Ching-Lung Su, Wei‐Ren Chen · 2019
This paper will develop a driving behavior monitoring system that applies a single near-infrared camera to record the driver, detect facial position and convolutional neural network through image recognition for judging whether the driver fatigues, smokes, and uses mobile devices or not. This system employs the NXP S32V234 processor with car grade so as to simultaneously identify a variety of driving behaviors and gaze position of drivers' eyesight. In addition, this system adopts the dual-core APEX-2 visual accelerator to accelerate the mask operation of convolutional neural network and traditional image processing. Comparing to only using CPU, the total average optimization speed is increased by 5 times before optimization.