Head Pose Estimation and Augmented Reality Tracking: An Integrated System and Evaluation for Monitoring Driver Awareness

By Erik Murphy-Chutorian, Mohan Manubhai Trivedi. IEEE transactions on intelligent transportation systems (Print), 2010

302 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach (2019, background): “To understand the driver behaviors, most of the studies require capturing the driver status information, such as the head pose [13], eye gaze [8], hand motion [14], foot dynamics [15], and even the physiological signals [16], [17].”
Detecting Driver Drowsiness Based on Sensors: A Review (2012, background): “However, research on using other behavioral measures, such as yawning [51] and head or eye position orientation [52,53], to determine the level of drowsiness is ongoing (Table 2).”