Camera Calibration using Neural Network for Image-Based Soil Deformation Measurement Systems

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. Copyright © 2008 by ASTM International.

Department(s)

Civil, Architectural and Environmental Engineering

Comments

University of Missouri, Grant None

Keywords and Phrases

Camera calibration; Neural network; Particle image velocimetry

International Standard Serial Number (ISSN)

0149-6115

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2024 ASTM International, All rights reserved.

Publication Date

01 Mar 2008

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