Paper Title:
Camera Calibration with Neural Networks
  Abstract

As the existence of the many unwanted factors, such as radial distortion and decentering distortion, the model of camera imaging is actually a nonlinear one. In order to successfully realize this kind of nonlinear mapping relationship between the 3D object points and their corresponding 2D image points, neural networks were and are still used. This paper introduced the history of camera calibration with neural network, covered the three types of neural network algorithms that have been used in camera calibration and explained their advantages as well as drawbacks with experiment results. After that, two issues that should be noted before and after the use of neural network were discussed and finally, the concluding remarks were gained.

  Info
Periodical
Edited by
Honghua Tan
Pages
2762-2767
DOI
10.4028/www.scientific.net/AMM.29-32.2762
Citation
Z. Tian, J. L. Xiong, Q. Zhang, "Camera Calibration with Neural Networks", Applied Mechanics and Materials, Vols. 29-32, pp. 2762-2767, 2010
Online since
August 2010
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