This paper describes an alternative approach to giving people with limited hand and arm movement the ability to select objects on a computing device using head movement (head mouse). To allow for better filtering of unintentional head movement, and to allow for a faster update rate of the head mouse, the full six-DoF pose of the head is estimated using a low-cost camera and IR markers, a 3-axis accelerometer, and a 3-axis magnetometer. The pose estimation problem was cast in a probabilistic fashion in which information from the different sensors is fused into a single a-posteriori distribution for the sensor pose. Simulations were run to analyze the influence of the proposed sensor fusion algorithm on the stability and accuracy of the pose estimation, and thus on the ability to point a mouse cursor to a specified location on a screen. Experiments were then performed validating the results from the simulations on real sensors. The proposed algorithm was shown to give more accurate and stable results than using only a camera to estimate the six-DoF pose.
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