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Calibration modeling for mobile vision based laser imaging and approximation networks

机译:基于移动视觉的激光成像和逼近网络的校准模型

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摘要

A mobile calibration technique for three-dimensional vision is presented. In this technique, the parameters of mobile vision are computed automatically by approximation networks and image processing of a laser line. Also, the three-dimensional vision is performed by the networks. The proposed vision system provides online geometric modifications from the initial configuration. Here, an online re-calibration is performed via network data to determine the setup modifications. Thus, vision limitations caused by the geometric modifications are overcome. The network is built based on the behavior of the laser line and the camera position. In this manner, the network provides the data for the automatic re-calibration. This system avoids calibrated references and external procedures for re-calibration. Therefore, the calibration model improves the accuracy and performance of the mobile vision. It is because the external data are not passed to the procedure of the three-dimensional vision. This kind of modeling represents a contribution for calibration of mobile vision. To elucidate this contribution an evaluation is carried out based on the calibration via perspective projection model. The time processing is also described.
机译:提出了一种用于三维视觉的移动校准技术。在这种技术中,移动视觉的参数是通过近似网络和激光线的图像处理自动计算出来的。而且,三维视觉是由网络执行的。所提出的视觉系统从初始配置提供在线几何修改。在此,通过网络数据执行在线重新校准以确定设置修改。因此,克服了由几何修改引起的视觉限制。该网络是根据激光线的行为和摄像机位置建立的。以这种方式,网络提供用于自动重新校准的数据。该系统避免了校准参考和外部校准过程。因此,校准模型提高了移动视觉的准确性和性能。这是因为外部数据没有传递到三维视觉的过程。这种建模代表了对移动视觉校准的贡献。为了阐明这一贡献,基于校准的透视投影模型进行了评估。还描述了时间处理。

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