Camera calibration with known rotation, Jan-Michael Frahm
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Jan-Michael Frahm
Research Assistant Professor
Department of Computer Science
University of North Carolina at Chapel Hill

Tel: (919) 962 1703
Fax: (919) 962 1699
Tutorials & Workshops

Camera-Selfcalibration with additional sensory information

The subject of camera selfcalibration is the computation of the internal camera parameters like focal length, aspect ratio, pricipal point, and skew. All these approaches tend to fit to noise.

Our appraoch is to use additonal orientation information to improve the selfcalibration. Our work shows that in case of a rotating camera the camera calibration problem is linear even in the case that all intrinsic parameters vary (Ph. D. thesis, ICCV 2003). For arbitrarily moving cameras the calibration problem is also linear but underdetermined for the general case of varying all intrinsic parameters. However, if certain constraints are applied to the intrinsic parameters the camera calibration can be computed linearily. 
image from calibration sequence
chart: calibration results
Image from sequence with 200 frames
Calibration result with mean absolute error of 3%

Furthermore we analyzed the robustness of the linear calibration. To improve the reliability of this linear calibration we used a maximum a posterori estimation which uses the linear calibration as an initial value (DAGM 2003).