What Can Be Predicted from Six Seconds of Driver Glances?

no code implementations • 26 Nov 2016 • Lex Fridman, Heishiro Toyoda, Sean Seaman, Bobbie Seppelt, Linda Angell, Joonbum Lee, Bruce Mehler, Bryan Reimer

We consider a large dataset of real-world, on-road driving from a 100-car naturalistic study to explore the predictive power of driver glances and, specifically, to answer the following question: what can be predicted about the state of the driver and the state of the driving environment from a 6-second sequence of macro-glances?

Binary Classification Gaze Estimation

Owl and Lizard: Patterns of Head Pose and Eye Pose in Driver Gaze Classification

no code implementations • 17 Aug 2015 • Lex Fridman, Joonbum Lee, Bryan Reimer, Trent Victor

The main insight of the paper is conveyed through the analogy of an "owl" and "lizard" which describes the degree to which the eyes and the head move when shifting gaze.

Classification General Classification

Driver Gaze Region Estimation Without Using Eye Movement

no code implementations • 16 Jul 2015 • Lex Fridman, Philipp Langhans, Joonbum Lee, Bryan Reimer

In theory, vision-based tracking of the eye can provide a good estimate of gaze location.