Abstract
Structural parameter calibration for the binocular stereo vision sensor (BSVS) is an important guarantee for high-precision measurements. We propose a method to calibrate the structural parameters of BSVS based on a double-sphere target. The target, consisting of two identical spheres with a known fixed distance, is freely placed in different positions and orientations. Any three non-collinear sphere centres determine a spatial plane whose normal vector under the two camera-coordinate-frames is obtained by means of an intermediate parallel plane calculated by the image points of sphere centres and the depth-scale factors. Hence, the rotation matrix R is solved. The translation vector T is determined using a linear method derived from the epipolar geometry. Furthermore, R and T are refined by nonlinear optimization. We also provide theoretical analysis on the error propagation related to the positional deviation of the sphere image and an approach to mitigate its effect. Computer simulations are conducted to test the performance of the proposed method with respect to the image noise level, target placement times and the depth-scale factor. Experimental results on real data show that the accuracy of measurement is higher than 0.9‰, with a distance of 800 mm and a view field of 250 × 200 mm2.
Highlights
As one of the main structures of machine vision sensors, binocular stereo vision sensor (BSVS) acquires 3D scene geometric information through one pair of images and has many applications in industrial product inspection, robot navigation, virtual reality, etc. [1,2,3]
Current calibration methods can be roughly classified into three categories: methods based on 3D targets, 2D targets and 1D targets. 3D target-based methods [4,5] obtain the structural parameters by placing the target only once in the sensor field of view
We describe a method to calibrate structural parameters
Summary
As one of the main structures of machine vision sensors, BSVS acquires 3D scene geometric information through one pair of images and has many applications in industrial product inspection, robot navigation, virtual reality, etc. [1,2,3]. Agrawal et al [11] and Zhang et al [16] both used spheres to calibrate intrinsic camera parameters using the relationship between the projected ellipse of the sphere and the dual image of the absolute conic (DIAC) They mentioned that the structural parameters between two or more cameras could be obtained by using the 3D points cloud registration method. We propose a method using a double-sphere target to calibrate the structural parameters of BSVS. We obtained its normal vector by an intermediate plane paralleling to the plane πs , which is recovered by the depth-scale factors and the image points of sphere centres.
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