Precise calibration of binocular vision system used for vision measurement

Abstract

Binocular vision calibration is of great importance in 3D machine vision measurement. With respect to binocular vision calibration, the nonlinear optimization technique is a crucial step to improve the accuracy. The existing optimization methods mostly aim at minimizing the sum of reprojection errors for two cameras based on respective 2D image pixels coordinate. However, the subsequent measurement process is conducted in 3D coordinate system which is not consistent with the optimization coordinate system. Moreover, the error criterion with respect to optimization and measurement is different. The equal pixel distance error in 2D image plane leads to diverse 3D metric distance error at different position before the camera. To address these issues, we propose a precise calibration method for binocular vision system which is devoted to minimizing the metric distance error between the reconstructed point through optimal triangulation and the ground truth in 3D measurement coordinate system. In addition, the inherent epipolar constraint and constant distance constraint are combined to enhance the optimization process. To evaluate the performance of the proposed method, both simulative and real experiments have been carried out and the results show that the proposed method is reliable and efficient to improve measurement accuracy compared with conventional method.

Calibrate Multiple Consumer RGB-D Cameras for Low-Cost and Efficient 3D Indoor Mapping

“…The IR and color optical sensors inside the Kinect V2 could be modeled using the pinhole camera model and solved by well-established RGB camera calibration methods [9,34,37]. The calibration of the relative pose parameters between the IR and RGB cameras is similar to stereo-camera calibration that could be solved by measuring geometrical targets in the shared FOV (e.g., 2D planar pattern [38,39], circle grid [40], 1D target [41,42]), appearance-based methods [43], or self-calibration used in robot navigation [44][45][46]. For depth calibration, additional depth error models based on 3D look-up tables [47,48] interpolating the related deviations, or on curve approximation with single/multiple B-splines [49,50] or polynomials [49] to model the distance deviations have been designed to enhance the quality of depth data.…”

Epipolar constraint of single-camera mirror binocular stereo vision systems

“…[14][15][16][17] Thus, the two real cameras are replaced by virtual cameras formed by a single camera and mirrors. 18 For a single-camera mirror system, the region of interest (ROI) usually covers the entire image, which significantly increases the matching error. To establish the geometric principles of the feature-matching process of a single-camera mirror binocular stereo vision system, we derived the epipolar constraint between two image parts for a single-camera model.…”

Three Degrees of Freedom Global Calibration Method for Measurement Systems with Binocular Vision

“…It provides flourishing developments in motion parameters testing, measurement of machine parts, parameter detection of micro-operating systems, 3D profile reconstruction [4][5][6][7], etc. It also gradually permeates into the aerospace, robot navigation, industrial measurement and bio-medical areas [8][9][10][11][12][13]. System calibration is the basis for binocular vision to obtain 3D coordinates.…”

“…However, it cannot deal with the occlusion and depth-related problems [28,29]. A 2D calibration object was reported to calibrate a binocular vision system used for vision measurement [12]. A precise calibration method was proposed for a binocular vision system which is devoted to minimizing the metric distance error between the reconstructed point and the real point in a 3D measurement coordinate system.…”