Camera pose estimation algorithm involving weighted measurement uncertainty of feature points based on rotation parameters

To solve the perspective-n-point problem in visual measurement, we present a camera pose estimation algorithm involving weighted measurement uncertainty based on rotation parameters. The method does not involve the depth factor, and the objective function is converted into a least-squares cost function that contains three rotation parameters. Furthermore, the noise uncertainty model enables a more accurate estimated pose, which can be directly calculated without initial values. Experimental results prove the high accuracy and good robustness of the proposed method. In the space of 1.5 m × 1.5 m × 1.5 m, the maximum estimation errors of rotation and translation are better than 0.04^◦ and 0.2%.