Abstract:The key of monocular vision based 3D displacement measurement is to obtain the camera pose parameters, which can be achieved by solving a perspective n points (PnP) problem. In order to improve the accuracy of PnP algorithm, this paper proposes an improved weighted Iterative EPnP algorithm (WIEPnP). WIEPnP intends to reduce the influence from sign point depth and image noise on the algorithm performance. It is done by setting weight coefficients for sign points and then conducting iterative calculations. MATLAB simulation experiments were carried out for comparative study with 6 PnP algorithms. The results show that the newly proposed WIEPnP can effectively reduce the impacts from the sign point depth and the effect of image Gaussian noise, respectively; and its accuracy and computation time satisfy the field application requirements. Later, the prototype experiments also verify the effectiveness of WIEPnP. In the prototype experiments, measurement errors in x and y directions are convinced to be less than 1 mm. In terms of z direction, the WIEPnP algorithm can effectively reduce the effect of depth changes; thus, the absolute error in z direction is restricted to no more than 3 mm. It can be seen that the WIEPnP algorithm proposed in this paper has good performance in terms of realtime and error; and it can meet the requirements for most realtime 3D displacement measurement.