Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation

Simon Baker, Iain Matthews, Jing Xiao, Ralph Gross, Takeo Kanade, and Takahiro Ishikawa
11th World Congress on Intelligent Transportation Systems, October, 2004.


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Abstract
The non-rigid motion of a driver's head (i.e. the motion of their mouth, eye-brows, cheeks, etc) can tell us a lot about their mental state; e.g. whether they are drowsy, alert, aggressive, comfortable, tense, distracted, etc. In this paper, we describe our recent research on non-rigid face tracking. In particular, we present both 2D and 3D algorithms for tracking the non-rigid motion of the driver's head using an Active Appearance Model. Both algorithms operate at over 200 frames per second. We also present algorithms for converting a 2D model into a 3D model and for fitting with occlusion and large pose variation.

Notes


Notes
Sponsor: DENSO CORPORATION
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Vision for Safe Driving and People Image Analysis Consortium
Associated Project(s): AAM Fitting Algorithms

Text Reference
Simon Baker, Iain Matthews, Jing Xiao, Ralph Gross, Takeo Kanade, and Takahiro Ishikawa, "Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation," 11th World Congress on Intelligent Transportation Systems, October, 2004.

BibTeX Reference
@inproceedings{Baker_2004_4704,
   author = "Simon Baker and Iain Matthews and Jing Xiao and Ralph Gross and Takeo Kanade and Takahiro Ishikawa",
   title = "Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation",
   booktitle = "11th World Congress on Intelligent Transportation Systems",
   month = "October",
   year = "2004",
}