This is a topic area of high potential for significant societal impact. Therefore, several projects do a small part of the greater system we envision. For instance, Driver Distraction Detection Using Single Convolutional Neural Network[2] explores monitoring detecting distracted driving using neural networks. Driver Distraction Detection and Recognition Using RGB-D Sensor[3] has a similar experiment, however they restrict phone detect to the driver’s arm location being next to their ear instead of monitoring the actual spatial displacement of the device itself.
Additionally, some of the specific components have had individual deep dives, especially in the area of facial recognition. Eye Blink Detection with OpenCV, Python, and Dlib[4] evaluates how to be detect eye blinking in a streaming computer frame using Python and some well-established libraries. Similarly, Head Pose Estimation Using OpenCV and Dlib[5] explores similar technologies except in terms of head positioning.
There remains an opportunity to combine these systems and add to them, to increase the precision and consistency of detection, that this system explores.
This project goes further than the former projects by combining several types of distracted behaviors and reporting it back to the driver so they can take corrective action. We also added monitors to devices, like a mobile phone, that are typically found in vehicles to create a holistic safe driving system.
Additionally, some of the specific components have had individual deep dives, especially in the area of facial recognition. Eye Blink Detection with OpenCV, Python, and Dlib[4] evaluates how to be detect eye blinking in a streaming computer frame using Python and some well-established libraries. Similarly, Head Pose Estimation Using OpenCV and Dlib[5] explores similar technologies except in terms of head positioning.
There remains an opportunity to combine these systems and add to them, to increase the precision and consistency of detection, that this system explores.
This project goes further than the former projects by combining several types of distracted behaviors and reporting it back to the driver so they can take corrective action. We also added monitors to devices, like a mobile phone, that are typically found in vehicles to create a holistic safe driving system.