Abstract
This paper presents a novel human-computer interaction system that has the potential to be used for autonomous or safety assisted driving in future vehicles. Convolutional neural networks were built and used for single shot detection and blink detection. The single shot detection method has been used to accomplish the detection of dynamic targets. The blink detection is performed by feeding multiple images of open and closed eyes into the network for deep learning, and based on the learned data models can detect the open or closed state of the subject’s eyes. In addition, eye tracking technology is used to identify the direction of the driver’s gaze. The human-computer interaction system is empirically validated in a super-compact electric vehicle, and it can accurately detect external dynamic targets, while the driver can control the vehicle by blinking and gaze direction.
