Driver monitoring based on low-cost 3-D sensors

A solution for driver monitoring and event detection based on 3-D information from a range camera is presented. The system combines 2-D and 3-D techniques to provide head pose estimation and regions-of-interest identification. Based on the captured cloud of 3-D points from the sensor and analyzing the 2-D projection, the points corresponding to the head are determined and extracted for further analysis. Later, head pose estimation with three degrees of freedom (Euler angles) is estimated based on the iterative closest points algorithm. Finally, relevant regions of the face are identified and used for further analysis, e.g., event detection and behavior analysis. The resulting application is a 3-D driver monitoring system based on low-cost sensors. It represents an interesting tool for human factor research studies, allowing automatic study of specific factors and the detection of special event related to the driver, e.g., driver drowsiness, inattention, or head pose.

driver monitoring; face detection; head pose estimation; iterative closest points (icp); point clouds; face recognition; iterative methods; driver monitoring; driver monitoring system; head pose estimation; iterative closest point; iterative closest points algorithms; point cloud; regions of interest; three degrees of freedom; image recognition

Driver monitoring based on low-cost 3-D sensors Articles