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Carnegie Mellon Robotics Institute

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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",
}

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