Title :
An Improved Iterative Solution to the PnP Problem
Author :
Jingyi Gao ; Yalin Zhang
Author_Institution :
State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China
Abstract :
The PnP (perspective-n-point) problem is very important in pose estimation technique based on computer vision. Aiming at this issue, an improved iterative solution is proposed. By the means of expressing the 3D point coordinates as a weighted sum of four control points, a system of homogeneous linear equations was established and then the optimized projections on the normalized image plane were obtained. The final estimation result was achieved by a relaxation-based iterative approach. Both simulations and experiments certify that the proposed algorithm can improve the computing accuracy and depress the image noise. Compared with other solutions to the PnP problem, the proposed algorithm can reduce the computational complexity while maintaining high precision with noise depression capability.
Keywords :
computational complexity; iterative methods; pose estimation; 3D point coordinates; PnP problem; computational complexity; computer vision; homogeneous linear equations; iterative solution; noise depression capability; normalized image plane; optimized projections; perspective-n-point; pose estimation technique; relaxation-based iterative approach; Cameras; Equations; Estimation; Iterative methods; Mathematical model; Noise; Three-dimensional displays; iterative solution; perspective-n-point problem; pose estimation;
Conference_Titel :
Virtual Reality and Visualization (ICVRV), 2013 International Conference on
Conference_Location :
Xi´an
DOI :
10.1109/ICVRV.2013.41