Assessment of camera models for use in planar velocimetry calibration
The performance of three implementations of pinhole-based camera models for use in common light-sheet imaging arrangements is investigated on the background of application to particle image velocimetry (PIV) and Doppler global velocimetry (DGV). Calibration data obtained from translated planar calibration targets was found to yield camera attitude within 0.1° on four different test cases with object distance varying as little as 2% depending on the choice of camera model. Camera calibration using data from a single image of coplanar points is considered a viable alternative to manual triangulation of camera positions but is restricted to off-normal viewing directions.
KeywordsDigital imaging Camera calibration Camera model Flow imaging Image transformation Doppler global velocimetry Stereo particle image velocimetry
The author likes to thank the PIV-Challenge steering committee, in particular Prof. M. Stanislas and Prof. J. Westerweel, for permission to use the stereo PIV image calibration data for this investigation. Further acknowledgments are given to B. Wieneke and D. Michaelis (LaVision, Germany) as well as C. Lempereur (ONERA, France) for initial information on the camera models and their pinhole positions. The suggestions made by the reviewers are greatly appreciated.
- Abdel-Aziz YI, Karara HM (1971) Direct linear transformation into object space coordinates in close-range photogrammetry. In: Proceedings of symposium on close-range photogrammetry, Urbana, pp 1–18Google Scholar
- Bouguet JY (1998) Camera calibration toolbox for matlab. Online at URL: http://www.vision.caltech.edu/bouguetj/calib_doc/
- van Doorne CWH (2004) Stereoscopic PIV on transition in pipe flow. PhD Thesis, Technical University Delft, The NetherlandsGoogle Scholar
- van Doorne CWH, Westerweel J (2006) Measurement of laminar, transitional and turbulent pipe flow using stereoscopic-PIV. Exp Fluids (submitted)Google Scholar
- Faugeras OD, Toscani G (1987) Camera calibration for 3-D computer vision. In: Proceedings of international workshop on industrial application for machinevision and machine intelligence, Silken, pp 240–247Google Scholar
- Fournel T, Lavest JM, Coudert S, Collange F (2004) Self-calibration of PIV video cameras in Scheimpflug condition. In: Stanislas M, Westerweel J, Kompenhans J (eds) Particle image velocimetry: recent improvements. Proceedings of the EUROPIV 2 Workshop, Zaragoza (Spain), March/April 2003. Springer, Berlin Heidelberg NewYork, pp 391–405Google Scholar
- Heikkilä J, Silvén O (1997) A four-step camera calibration procedure with implicit image correction. In: Proceedngs of international conference on computer vision and pattern recognition 97. IEEE Computer Society Press, Toronto, pp 1106–1112Google Scholar
- McCullagh B, Shevlin F (2004) Coplanar camera calibration with small depth of field lens. In: Proceedings of Irish machine vision and image processing IMVIP 2004, DublinGoogle Scholar
- Sturm PF, Maybank SJ (1999) On plane-based camera calibration: a general algorithm, singularities, applications. In: Proceedings of IEEE computer vision and pattern recognition conference, Ft. Collins, June, pp 432–437Google Scholar
- Tsai RY (1986) An efficient and accurate camera calibration technique for 3D machine vision. In: Proceedings of IEEE conference on computer vision and pattern recognition, Miami Beach, pp 364–374Google Scholar
- Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1992) Numerical recipes in C—2nd edn. Cambridge University Press, Cambridge. ISBN 0-521-43108-5, pp 681–688Google Scholar
- Willson R (1995) Tsai camera calibration software. C code for Tsai calibration. Online at URL: http://www.cs.cmu.edu/∼rgw/TsaiCode.html