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A Novel Approach to Calibrating Multifunctional Binocular Stereovision Sensor

机译:一种校准多功能双目立体宽度传感器的新方法

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We present a novel multifunctional binocular stereovision sensor for various three-dimensional (3D) inspection tasks. It not only avoids the socalled correspondence problem of passive stereo vision, but also possesses the uniform mathematical model. We also propose a novel approach to estimating all the sensor parameters with free-position planar reference object. In this technique, the planar pattern can be moved freely by hand. All the camera intrinsic and extrinsic parameters with coefficient of lens radial and tangential distortion are estimated, and sensor parameters are calibrated based on the 3D measurement model and optimized with the feature point constraint algorithm using the same views in the camera calibration stage. The proposed approach greatly reduces the cost of the calibration equipment, and it is flexible and practical for the vision measurement. It shows that this method has high precision by experiment, and the sensor measured relative error of space length excels 0.3%.
机译:我们为各种三维(3D)检查任务提供了一种新型多功能双目立体宽度传感器。它不仅避免了被动立体声视觉的被动对应问题,而且还具有统一的数学模型。我们还提出了一种新颖的方法来估计具有自由位置平面参考对象的所有传感器参数。在该技术中,平面图案可以手动自由移动。估计具有系数透镜系数和切向失真的相机内在和外在参数,并且基于3D测量模型校准传感器参数,并在相机校准阶段中使用相同的视图与特征点约束算法进行了优化。所提出的方法大大降低了校准设备的成本,并且对于视觉测量,它是灵活实用的。结果表明,该方法通过实验具有高精度,传感器测量空间长度的相对误差优于0.3%。

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