Study on multi-cameras and structured-light vision system calibration approach study in large filed view measurement

被引:0
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作者
School of Electrical Engineering, Southwest Jiaotong University, Chengdu [1 ]
610031, China
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来源
Yi Qi Yi Biao Xue Bao | / 4卷 / 903-912期
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Linear transformations;
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摘要
The global calibration of multi-cameras and structured-light vision system is the key issue in the high-accuracy profiling measurement of large field of view due to wide camera distribution, lacking common field of view among the cameras and complicated calibration model for multiple cameras. In this paper, a novel calibration approach for multicameras and structured-light vision system is proposed, which only requires one 2D planar target and one 1D target. The intrinsic and extrinsic parameters of the cameras are calibrated off-line and on-line, respectively. Firstly, different types of lens distortions, including lens radial distortion, tangential distortion and thin prism distortion, are considered, and the intrinsic parameters of the cameras are calibrated according to the planar target feature points. Then, selecting one camera coordinate frame as the global coordinate frame, the 1D target is moved freely in the field of view of neighboring cameras, and the rotation matrix and translation vector for every neighboring camera are computed based on the co-linearity property and the known distances of the feature points on the 1D target. The transformation from each camera local coordinate frame to the global coordinate frame is realized by utilizing the above neighboring camera rotation matrix and translation vector. Similarly, the laser plane equation in the global coordinate frame is acquired with at least three non-collinear points on the laser plane using the 1D target. Finally, the global measurement model is set up through integrating the intrinsic parameters, the extrinsic parameters and the laser plane equation in the global coordinate frame. Both the calibration experiment and field application results demonstrate the effectiveness and feasibility of the proposed algorithm. ©, 2015, Science Press. All right reserved.
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