A Monocular Vision Relative Displacement Measurement Method Based on Bundle Adjustment Optimization and Quadratic Function Correction

Abstract

In order to meet the requirements of high-precision target displacement measurement, this paper proposed a measurement method based on monocular vision measurement system by which the advantages of simple structure, convenient debugging, easy to install and calibrate is recognized. This method first uses the bundle adjustment algorithm with conditional constraints to optimize the solution results of the orthogonal iterative algorithm, then calculates the relative poses of the optimization results, finally establishes an error correction model to perform secondary optimization on the relative poses. The experimental results show that the method proposed in this paper can reduce more than 54% average error of displacement measurement results, and the error between the final displacement measurement results and the actual displacement values is controlled at 0.4mm level, which proves that the method has good practical value.

Sensing Algorithm to Estimate Slight Displacement and Posture Change of Target from Monocular Images

“…The method using monocular vision, it estimates the position and the orientation of object from its images captured by a single camera [ 8 , 9 , 10 ]. In [ 8 ], a sampling moiré method is used to measure the displacement in the z -direction with 30 μm error for 20 cm distance, but it assumes that the displacement in the x - y direction is negligibly small.…”

“…In [ 8 ], a sampling moiré method is used to measure the displacement in the z -direction with 30 μm error for 20 cm distance, but it assumes that the displacement in the x - y direction is negligibly small. In [ 9 ], the displacement is estimated with an error of about 0.4 mm for a target with a distance of 1000 mm. However, the results of the posture measurements are not shown.…”