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RI | Publications | Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation
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Text only version of this site
Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation
S. Baker, I. Matthews, J. Xiao, R. Gross, T. Ishikawa, and T. Kanade
tech. report CMU-RI-TR-04-10, Robotics Institute, Carnegie Mellon University, February, 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 |
Associated center: VASC
Associated labs/groups: People Image Analysis Consortium, Vision for Safe Driving, Face Group, and Human Sensing
Associated project: AAM Fitting Algorithms
| Text Reference |
S. Baker, I. Matthews, J. Xiao, R. Gross, T. Ishikawa, and T. Kanade, Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation, tech. report CMU-RI-TR-04-10, Robotics Institute, Carnegie Mellon University, February, 2004.
| BibTeX Reference |
@techreport{Baker_2004_4598,
author = "Simon Baker and Iain Matthews and Jing Xiao and Ralph Gross and Takahiro Ishikawa and Takeo Kanade",
title = "Real-Time Non-Rigid Driver Head Tracking for Driver Mental State Estimation",
institution = "Robotics Institute, Carnegie Mellon University",
month = "February",
year = "2004",
number = "CMU-RI-TR-04-10",
address = "Pittsburgh, PA"
}