As to pose measurement technology based on visual image, the global convergence of the nonlinear algorithm is uncertain, and the results depend on the selection of initial values, so the robustness of pose measurement cannot be guaranteed. Linear pose measurement algorithms have relatively high requirements for image processing. If the image coordinates of feature points are not accurately extracted, the pose measurement accuracy will be reduced. On the condition of natural light, the camera collects the image of positioning feature points, and the existence of high light regions in the image have some impacts on the extraction accuracy of feature points, which reduces the number of effective feature points and affects the pose measurement accuracy. To solve the problems above, a linear pose measurement method based on the optimal polarization angle was proposed. The camera was equipped with a polarizer. The optimal polarization angle solution model was established according to the Stokes vector. On the premise of the optimal polarization angle, the feature points images were collected and the image coordinates of the feature points were extracted. The linear solving model was established to solve the object pose. The experimental results show that this method can effectively reduce the high light regions in the image, which improve the imaging quality and improve the linear pose measurement accuracy. In the measurement range of -60° to +60°, the angle measurement error is less than ±0.16°. In the measurement range of 0 to 20 mm, the displacement measurement error is less than ±0.05 mm.