Design of an attention detection system on the Zynq-7000 SoC
Fynn Schwiegelshohn, Michael K. Hubner · 2014
In this paper, we introduce a prototype attention detection system for automotive drivers. The driver is monitored through a Microsoft Kinect camera which provides RGB, depth, and infrared images in order to cover situations in which normal cameras might not achieve good results. The Kinect is connected to a Xilinx ZedBoard wich uses a Zynq-7000 SoC as processing platform. The attention detection system is running on the ARM Cortex-A9 dual core processor of the Zynq-7000 SoC. The system needs to recognize the drivers face and eyes in order to determine his state of attention. If the driver is classified as being attentive, no warning is generated. If the driver is classified as being inattentive, the system will generate a warning. Several algorithmic optimizations have been implemented in order to increase performance of this solution. In order to simulate a realistic driving environment, we have connected the Xilinx ZedBoard with a car simulator. This provides us with the necessary real world data to validate our system design. When our detection system classifies a driver as distracted or drowsy, it will send a warning message to the car simulator. The results show that the system performs satisfactorily when a face is detected. However, if no face is detected, the frame rate drops below an acceptable level.