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High-precision binocular camera calibration method based on a 3D calibration object
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A high-precision binocular camera calibration method is proposed to address the issues of poor calibration accuracy and large calibration errors in current practical applications. This method uses a triangular stereo sphere as the calibration object and employs steps, such as ellipse fitting, Cholesky decomposition, homography matrix solution, and nonlinear optimization, to compute the intrinsic and extrinsic parameters, distortion parameters, and relative pose of the binocular camera. Moreover, this method simplifies the correspondences between primitives, enabling simultaneous calibration of multiple viewpoint cameras. This method is also suitable for both binocular cameras consisting of two different structured monocular cameras and those composed of two image sensors within the same structure. Experimental results showed that this method outperforms traditional algorithms in terms of binocular camera calibration accuracy, calibration errors between left and right cameras, and robustness, resulting in a significant improvement in overall algorithm performance.
Title: High-precision binocular camera calibration method based on a 3D calibration object
Description:
A high-precision binocular camera calibration method is proposed to address the issues of poor calibration accuracy and large calibration errors in current practical applications.
This method uses a triangular stereo sphere as the calibration object and employs steps, such as ellipse fitting, Cholesky decomposition, homography matrix solution, and nonlinear optimization, to compute the intrinsic and extrinsic parameters, distortion parameters, and relative pose of the binocular camera.
Moreover, this method simplifies the correspondences between primitives, enabling simultaneous calibration of multiple viewpoint cameras.
This method is also suitable for both binocular cameras consisting of two different structured monocular cameras and those composed of two image sensors within the same structure.
Experimental results showed that this method outperforms traditional algorithms in terms of binocular camera calibration accuracy, calibration errors between left and right cameras, and robustness, resulting in a significant improvement in overall algorithm performance.
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