3D Head pose estimation and camera mouse implementation using a monocular video camera

In this paper, we present a novel approach to estimate 3D head pose using a monocular video camera for the control of mouse pointer and generating clicking events. Our approach proceeds in four stages. First, the face area is detected using Haar-like features and AdaBoost algorithm. Second, the point features are extracted and tracked over video frames by KLT algorithm. Third, by employing the tracked point features and 2D motion model of the face area, we estimate the 3D rotation matrix and translation vector between web camera and the head position. Finally, the 3D rotation matrix and translation vector are employed to calculate the mouse pointer location on the PC screen and generating clicking events. Furthermore, we propose eye wink detection as an alternative for clicking event implementation.

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