Corrected calibration algorithm with a fixed constraint relationship and an error compensation technique for a binocular vision measurement system.

This paper is concerned with the precise calibration algorithm and error compensation technique for a binocular vision measurement system. By invoking a fixed constraint relationship between the binocular cameras, these two cameras can be preferably bound together as one camera, which means that in each iteration only one camera needs external parameter tuning for optimized encapsulation, and the iteration time is reduced. The global optimal solutions are obtained by substituting the initial iterative solutions into the optimized iterative equations of the spatial points. The derived improved iterative algorithm obtains the camera parameters with high precision and performs better in noise resistance. Moreover, the error compensation matrix is constructed to correct the relative pose of binocular cameras, upon which solutions to the error compensation matrix are solved via the unit quaternion. Consequently, the relative pose matrix is revised, allowing for further improvement in the calibration performance. Finally, simulation and practical experiments are demonstrated. The relevant results confirm the precision and robustness of the proposed approach.