T. Horprasert, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
Y. Yacoob, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
L.S. Davis, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
An approach for estimating 3D head orientation in a monocular image sequence is proposed. The approach employs recently developed image-based parameterized tracking for face and face features to locate the area in which a sub-pixel parameterized shape estimation of the eye's boundary is performed. This involves tracking of five points (four at the eye corners and the fifth is the lip of the nose). The authors describe an approach that relies on the coarse structure of the face to compute orientation relative to the camera plane. Our approach employs projective invariance of the cross-ratios of the eye corners and anthropometric statistics to estimate the head yaw, roll and pitch. Analytical and experimental results are reported.
Index Terms:
face recognition; 3D head orientation computation; monocular image sequence; image-based parameterized tracking; face features; sub-pixel parameterized shape estimation; eye boundary; coarse structure; camera plane; projective cross-ratio invariance; anthropometric statistics; eye corners; head yaw; head roll; head pitch
Citation:
T. Horprasert, Y. Yacoob, L.S. Davis, "Computing 3-D head orientation from a monocular image sequence," fg, pp.242, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996
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