Title :
Head pose and gaze direction tracking for detecting a drowsy driver
Author :
In-Ho Choi ; Yong-Guk Kim
Author_Institution :
Dept. of Comput. Eng., Sejong Univ., Seoul, South Korea
Abstract :
This paper proposes a system that uses gaze direction tracking and head pose estimation to detect drowsiness of a driver. Head pose is estimated by calculating optic flow of the facial features, which are acquired with a corner detection algorithm. Analysis of the driver´s head behavior leads to three moving components: nodding, shaking, and tilting. To track the gaze direction of the driver, we trace the center point of the pupil using CDF analysis and estimate the frequency of eye-movement.
Keywords :
driver information systems; feature extraction; gaze tracking; human factors; image sequences; object tracking; pose estimation; CDF analysis; corner detection algorithm; driver head behavior analysis; drowsiness detection; drowsy driver detection; eye-movement frequency estimation; facial features; gaze direction tracking; head pose estimation; head pose tracking; nodding component; optic flow; shaking component; tilting component; Accuracy; Estimation; Feature extraction; Head; Three-dimensional displays; Vectors; Vehicles; Driver Drowsiness Detection; Eye Blinking; Gaze Direction; Head Pose Estimation;
Conference_Titel :
Big Data and Smart Computing (BIGCOMP), 2014 International Conference on
Conference_Location :
Bangkok
DOI :
10.1109/BIGCOMP.2014.6741444