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FGR
2008
IEEE

A discriminative approach to frame-by-frame head pose tracking

8 years 9 months ago
A discriminative approach to frame-by-frame head pose tracking
We present a discriminative approach to frame-by-frame head pose tracking that is robust to a wide range of illuminations and facial appearances and that is inherently immune to accuracy drift. Most previous research on head pose tracking has been validated on test datasets spanning only a small (< 20) subjects under controlled illumination conditions on continuous video sequences. In contrast, the system presented in this paper was both trained and tested on a much larger database, GENKI, spanning tens of thousands of different subjects, illuminations, and geographical locations from images on the Web. Our pose estimator achieves accuracy of 5.82◦ , 5.65◦ , and 2.96◦ root-meansquare (RMS) error for yaw, pitch, and roll, respectively. A set of 4000 images from this dataset, labeled for pose, was collected and released for use by the research community.
Jacob Whitehill, Javier R. Movellan
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where FGR
Authors Jacob Whitehill, Javier R. Movellan
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