Robust real-time 3D head pose estimation from range data

In this paper a real-time 3D pose estimation algorithm using range data is described. The system relies on a novel 3D sensor that generates a dense range image of the scene. By not relying on brightness information, the proposed system guarantees robustness under a variety of illumination conditions, and scene contents. Efficient face detection using global features and exploitation of prior knowledge along with novel feature localization and tracking techniques are described. Experimental results demonstrate accurate estimation of the six degrees of freedom of the head and robustness under occlusions, facial expressions, and head shape variability.

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