Similarity based linear n⩾5-point structure and pose estimation from it single image

We present a novel two-stage algorithm for structural and pose estimation from a single image. Our method is a significant improvement on the work described by Quan et al. (1999) because: our algorithm is developed in similarity space rather than in camera centred coordinate frame; our algorithm is directly based on a fourth order polynomial rather than on an eighth order polynomial resulting in an easier and more efficient implementation; and finally our algorithm is a unified linear algorithm for structural estimation. The algorithm has been extensively validated by experimentation using both synthetic and real images and compared with a classical linear algorithm and an algorithm based on epipolar geometry. Experimental results show that the proposed algorithm is generally accurate, robust, and efficient for the calibration of all parameters of interest