Pose estimation for camera calibration and landmark tracking

An algorithm is proposed for pose estimation based on the volume measurement of tetrahedra composed of feature-point triplets extracted from an arbitrary quadrangular target and the lens center of the vision system. Using a pinhole model (lens distortion is taken into account separately) and a quadrangular target, for which only the six distance measurements between all pairs of feature points are known, the complete pose is determined using an all-geometric closed-form solution for the six parameters of the pose (three translation components and three rotation components). This method has been tested using synthetic and real data and shown to be efficient, accurate, and robust. Its speed, in particular, makes it a potential candidate for real-time robotic tasks.<
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