Distance constraint based iterative structure and pose estimation from a single image

This paper presents a novel method for structural and pose estimation from 3D-2D correspondence. Structural data are obtained by first estimating the depths of some reference points using the Newton-Raphson method with a distance constraint followed by depth estimation of the remaining points in closed form solution. Pose estimation is obtained through the constraint least squares method which has been proven accurate and robust for noisy image data. Experimental results based on both synthetic data and real images have shown that the proposed algorithm is accurate and robust in the presence of noise.