Abstract
This paper investigates the prospective n-point (PnP) problem and provides an effective, dependable, and fast optimal solution. The challenging pose estimation problem is changed into the ideal circumstance for solving the transition matrix by estimating the position and orientation of the camera based on known reference points. This method meets both the geometric optimality and the statistical optimal solution by accounting for observation and propagation uncertainty in the solution process. In addition, in order to further optimize the error caused by the mapping process, this paper introduces the L-BFGS algorithm for optimal processing. It saves time and cost because it can iterate the optimal transition matrix and systematic error synchronously. In this paper, the algorithm simulation tests are carried out in the standard case, the quasi-singular case, and the planar case. The results of the experiments demonstrate that the strategy suggested in this paper can successfully address the issue of camera position estimation. Compared with the existing advanced technology, the accuracy is improved by about 8% - 13%, and the time cost is low.
Published Version
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