Camera calibration checkerboardonline

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Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University in Prague, Technicka 2, 166 27, Prague 6, Czech Republic

We present a new checkerboard detection algorithm which is able to detect checkerboards at extreme poses, or checkerboards which are highly distorted due to lens distortion even on low-resolution images. On the detected pattern we apply a surface fitting based subpixel refinement specifically tailored for checkerboard X-junctions. Finally, we investigate how the accuracy of a checkerboard detector affects the overall calibration result in multi-camera setups. The proposed method is evaluated on real images captured with different camera models to show its wide applicability. Quantitative comparisons to OpenCV’s checkerboard detector show that the proposed method detects up to 80% more checkerboards and detects corner points more accurately, even under strong perspective distortion as often present in wide baseline stereo setups.

Zhang, Z.: A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11), 1330–1334 (2000)

Camera calibration checkerboardOpenCV

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De la Escalera, A., Armingol, J.M.: Automatic chessboard detection for intrinsic and extrinsic camera parameter calibration. Sensors 10(3), 2027–2044 (2010)

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Fiala, M., Shu, C.: Self-identifying patterns for plane-based camera calibration. Machine Vision and Applications 19(4), 209–216 (2008)

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Wang, Z., Wu, W., Xu, X., Xue, D.: Recognition and location of the internal corners of planar checkerboard calibration pattern image. Applied Mathematics and Computation 185(2), 894–906 (2007)