Vision-based motion estimation for interaction with mobile devices

This paper introduces a novel interaction technique for handheld mobile devices which enables the user interface to be controlled by the motion of the user's hand. A feature-based approach is proposed for global motion estimation that exploits gradient measures for both feature selection and feature motion uncertainty analysis. A voting-based scheme is presented for outlier removal. A Kalman filter is applied for smoothing motion trajectories. A fixed-point implementation of the method was developed due to the lack of floating-point hardware. Experiments testify the effectiveness of the approach on a camera-enabled mobile phone.