Real Time Head Pose Tracking from Multiple Cameras with a Generic Model

Qin Cai, A. Sankaranarayanan, Q. Zhang, Zhengyou Zhang, and Zicheng Liu


We present a robust approach to real-time 3D head

pose tracking using multiple cameras with unknown camera

placements. Many important applications do not want prior

multi-camera calibration. We exploit a generic face model

to overcome the difficulties due to the lack of prior knowledge

of camera placement and the severe head appearance

difference across cameras. We propose a fast drift-free solution

based on feature point tracking using reference frames

of high confidence over the temporal and spatial domains.

Our algorithm tracks feature points from Harris feature detector,

but not necessarily points of face landmarks. The relative

camera placement is refined progressively at the same

time as the user’s head pose is resolved. Compared to single

camera tracking, the use of multiple cameras increases the

reliability of tracking by covering a wider range of poses

as well as providing more accurate head pose estimation.

We have tested the algorithm on many subjects in a variety

of environments. A live demonstration will be shown at the



Publication typeInproceedings
Published inIEEE Workshop on Analysis and Modeling of Faces and Gestures in conjunction with CVPR 2010
> Publications > Real Time Head Pose Tracking from Multiple Cameras with a Generic Model