New camera technology use facial cues to detect drunk drivers
How does the new camera technology detect drunk drivers?
The new camera technology developed by researchers at Edith Cowan University detects drunk drivers by analyzing facial cues from standard RGB videos of the driver's faces1. The machine learning system gauges the degree of alcohol-related impairment by examining facial features, gaze direction, and head position. The technology has the potential to be integrated into road cameras and applied to various vehicle types without specialized in-cabin installations.
What technology is Edith Cowan University developing?
Edith Cowan University is developing a new computer tracking technology that uses data from camera footage to detect whether a driver is impaired by alcohol. The system employs a machine learning algorithm that analyzes facial features, gaze direction, and head position from standard RGB videos of the driver's faces to assess the degree of alcohol-related impairment. The technology has the potential to be integrated into vehicles and smartphones for effective alcohol intoxication detection.
What data sources were used in the drunk driving detection study?
The drunk driving detection study used data from camera footage, capturing facial features, gaze direction, and head position of drivers under varying levels of alcohol intoxication. The research involved participants driving on a simulator and their behavior was recorded using standard RGB videos.