Camera Calibration Using Neural Network for Image-Based Soil Deformation Measurement Systems
Zhao H, Ge L
(Received 16 July 2006; accepted 3 August 2007)

Abstract

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.

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Author Zhao H, Ge L Title Camera Calibration Using Neural Network for Image-Based Soil Deformation Measurement Systems Symposium , Committee on