Novel Neural Networks for Camera Calibration in Underwater Environments

A novel method for camera calibration in underwater environments using convolutional networks is presented. Two modified neural network architectures, ZCalibAquaNet and BCalibAquaNet, were developed for calibration matrix estimation from chessboard images in underwater environments. The process bega...

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Veröffentlicht in:	IEEE access 2024-01, Vol.12, p.1-1
Hauptverfasser:	Sanchez-Saquin, Cristian H., Barriga-Rodriguez, Leonardo, Baldenegro-Perez, Leonardo A., Ronquillo-Lomeli, Guillermo, Rodriguez-Olivares, Noe A.
Format:	Artikel
Sprache:	eng
Schlagworte:	3D reconstruction Bouguet Bouquet Calibration calibration matrix Cameras Convolutional neural networks Distortion Error analysis Estimation Image reconstruction Neural networks Robot vision systems Solid modeling Three-dimensional displays Training Underwater Underwater calibration Zhang
Online-Zugang:	Volltext
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