ML Anthology

Camera Based Automatic Calibration for the Varrier-System

Jinghua Ge, Dan Sandin, Tom Peterka, Todd Margolis, Thomas A. DeFanti
CVPRW 2005 pp. 110
doi:10.1109/CVPR.2005.427 /cvprw/2005/ge2005cvprw-camera/

Abstract

Varrier is a head-tracked, 35-panel tiled autostereoscopic display system which is produced by The Electronic Visualization Laboratory (EVL) at the University of Illinois at Chicago (UIC). Varrier produces autostereoscopic imagery through a combination of a physical parallax barrier and a virtual barrier, so that the stereoscopic images are directed correctly into the viewer's eyes. Since a small amount of rotation and translation between physical and virtual barriers can cause large-scale effects, registration is critical for correct stereo viewing. The process is automated by examining image frames of two video cameras separated by the interocular distance as a simulation of human eyes. Three registration parameters for each panel are calibrated in the process. An arbitrary start condition is allowed and a robust stopping criterion is used to end the process and report results. Instead of exhaustive three dimensional searching, an efficient two phase calibration method is introduced. The combination of a heuristic rough calibration and an adaptive fine calibration guarantees a fast searching process with the best solution.

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Cite

Text

Ge et al. "Camera Based Automatic Calibration for the Varrier-System." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005. doi:10.1109/CVPR.2005.427

Markdown

[Ge et al. "Camera Based Automatic Calibration for the Varrier-System." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005.](https://mlanthology.org/cvprw/2005/ge2005cvprw-camera/) doi:10.1109/CVPR.2005.427

BibTeX

@inproceedings{ge2005cvprw-camera,
  title     = {{Camera Based Automatic Calibration for the Varrier-System}},
  author    = {Ge, Jinghua and Sandin, Dan and Peterka, Tom and Margolis, Todd and DeFanti, Thomas A.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2005},
  pages     = {110},
  doi       = {10.1109/CVPR.2005.427},
  url       = {https://mlanthology.org/cvprw/2005/ge2005cvprw-camera/}
}