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首页> 外文期刊>Geotechnical testing journal >Camera Calibration Using Neural Network For Image-based Soil Deformation Measurement Systems
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Camera Calibration Using Neural Network For Image-based Soil Deformation Measurement Systems

机译:基于图像的土壤变形测量系统的神经网络相机标定

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摘要

A neural network camera calibration algorithm has been adapted for image-based soil deformation measurement systems. This calibration algorithm provides a highly accurate prediction of object data points from their corresponding image points. The experimental setup for this camera calibration algorithm is rather easy, and can be integrated into particle image velocimetry (PIV) to obtain the full-field deformation of a soil model. The performance of this image-based measurement system was illustrated with a small-scale rectangular footing model This fast and accurate calibration method will greatly facilitate the application of an image-based measurement system into geotechnical experiments,
机译:神经网络摄像机校准算法已被适配用于基于图像的土壤变形测量系统。该校准算法可根据对象数据点的相应图像点提供高度准确的预测。该相机校准算法的实验设置非常简单,可以集成到粒子图像测速仪(PIV)中以获得土壤模型的全场变形。这个基于图像的测量系统的性能通过一个小规模的矩形基础模型进行了说明。这种快速,准确的校准方法将极大地促进基于图像的测量系统在岩土工程中的应用,

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