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"Owl' and "Lizard': patterns of head pose and eye pose in driver gaze classification

L. Fridman ; J. Lee ; B. Reimer ; Trent Victor (SAFER - Fordons- och Trafiksäkerhetscentrum )
Iet Computer Vision (1751-9632). Vol. 10 (2016), 4, p. 308-314.
[Artikel, refereegranskad vetenskaplig]

Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating the more effective study of how to improve (i) vehicle interfaces and (ii) the design of future advanced driver assistance systems. In this study, the authors estimate head pose and eye pose from monocular video using methods developed extensively in prior work and ask two new interesting questions. First, how much better can they classify driver gaze using head and eye pose versus just using head pose? Second, are there individual-specific gaze strategies that strongly correlate with how much gaze classification improves with the addition of eye pose information? The authors answer these questions by evaluating data drawn from an on-road study of 40 drivers. The main insight of the study 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. When the head moves a lot (owl'), not much classification improvement is attained by estimating eye pose on top of head pose. On the other hand, when the head stays still and only the eyes move (lizard'), classification accuracy increases significantly from adding in eye pose. The authors characterise how that accuracy varies between people, gaze strategies, and gaze regions.

Nyckelord: pose estimation, gaze tracking, driver information systems, video signal processing, image classification, head pose pattern estimation, eye pose pattern estimation, driver gaze classification, inexpensive gaze tracking, vehicle interfaces, future advan, Computer Science, Engineering

Denna post skapades 2016-09-07.
CPL Pubid: 241462


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SAFER - Fordons- och Trafiksäkerhetscentrum


Datorseende och robotik (autonoma system)

Chalmers infrastruktur