Multiple Camera Calibration using Robust Perspective Factorization

In this paper we address the problem of recovering structure and motion from a large number of intrinsically calibrated perspective cameras. We describe a method that combines (1) weak-perspective reconstruction in the presence of noisy and missing data and (2) an algorithm that updates weak-perspective reconstruction to perspective reconstruction by incrementally estimating the projective depths. The method also solves for the reversal ambiguity associated with affine factorization techniques. The method has been successfully applied to the problem of calibrating the external parameters (position and orientation) of several multiple-camera setups. Results obtained with synthetic and experimental data compare favourably with results obtained with non-linear minimization such as bundle adjustment.

@InProceedings\{ZHRL06,
  author       = "Zaharescu, Andrei and Horaud, Radu P. and Ronfard, Remi and Lefort, Loic",
  title        = "Multiple Camera Calibration using Robust Perspective Factorization",
  booktitle    = "Proceedings of the 3rd International Symposium on 3D Data Processing, Visualization and Transmission, Chapel Hill (USA)",
  pages        = "504-511",
  year         = "2006",
  publisher    = "IEEE Computer Society Press",
  url          = "http://perception.inrialpes.fr/Publications/2006/ZHRL06"
}