In conjunction with the advancing development
of driver assistance systems, driver observation becomes increasingly
important. This paper proposes a new approach for
driver’s head pose estimation. With a stereo camera mounted
in a realistic position on top of the center stack the system
continuously tracks the orientation of the driver’s head in realtime
(25fps) using solely 3-D information. The systems processing
chain comprises separate modules for head separation,
pose estimation and pose tracking. Head separation employes a
Bayesian modeling approach for robust head-torso separation.
The pose estimation module uses Synchronized Submanifold
Embedding (SSE), a nonlinear regression method, which includes
a dimensionality reduction, a k-nearest neighbor search
and a barycentric coordinate estimation. The tracking module
estimates angular velocity of the head, using an Extended
Kalman Filter (EKF) in quaternion space. Comprehensive
experiments show, that the proposed system achieves high accuracy
from a non-central camera position. Since the approach
does not rely on facial feature points the system handles large
pose variations and is not disturbed by (sun)glasses.