Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation

Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation

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by Erik Murphy-chutorian , Anup Doshi , Mohan Manubhai Trivedi

Citations:

20 - 13 self

BibTeX

@MISC{Murphy-chutorian_headpose,
    author = {Erik Murphy-chutorian and Anup Doshi and Mohan Manubhai Trivedi},
    title = {Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation},
    year = {}
}

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Abstract

Abstract — Recognizing driver awareness is an important prerequisite for the design of advanced automotive safety systems. Since visual attention is constrained to a driver’s field of view, knowing where a driver is looking provides useful cues about his activity and awareness of the environment. This work presents an identity- and lighting-invariant system to estimate a driver’s head pose. The system is fully autonomous and operates online in daytime and nighttime driving conditions, using a monocular video camera sensitive to visible and near-infrared light. We investigate the limitations of alternative systems when operated in a moving vehicle and compare our approach, which integrates Localized Gradient Orientation histograms with support vector machines for regression. We estimate the orientation of the driver’s head in two degrees-of-freedom and evaluate the accuracy of our method in a vehicular testbed equipped with a cinematic motion capture system. I.

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