It's better to spot drunk drivers as soon as they get in their car, not once they've already been dangerously driving the roads for some time. A new facial tracking system was created with that fact in mind, and it utilizes a regular in-vehicle video camera. Although there already are a number of experimental car-integrated setups for detecting intoxication in drivers, many utilize specialized equipment such as or even .
Others work by assessing drivers' driving patterns, potentially allowing those individuals to drive drunk as the data is still being gathered. In response to such limitations, scientists at Australia's Edith Cowan University set out to develop a system that could provide early intervention via conventional, inexpensive hardware. The researchers started out by having 60 volunteers use an indoor driving simulator while a conventional RGB (red, green, blue) video camera recorded footage of their face.
Each person drove at three successive levels of intoxication: Sober, Low and Severe. A machine-learning-based algorithm was then used to scrutinize the footage, looking for telltale visual characteristics exhibited by all (or at least most) of the test subjects at each of the three levels. It was found that certain facial movements, along with gaze direction and head position, were relatively consistent indicators.
When the algorithm was subsequently tested on more drunk-driving facial videos, it proved to be 75% accurate at determining which of the three levels ea.