Abstract
We describe here a method to compute the internal parameters of a camera whose position and orientation are known. The method is based on the observation of at least three conics on a known plane; these can be easily extracted in a real scenario from a tiled floor or other regular structures. The method estimates the principal point and focal length using a unique image of the conics when these are observed by an additional calibrated camera. Differently from other methods, no assumption is made on the conics used for calibration. The experimental results demonstrate that the accuracy of the method is comparable to that of more traditional (and time consuming) approaches. It can find applications in systems of Pan-Zoom-Tilt (PZT) or traditional cameras, that are nowadays widely employed, for instance in the surveillance domain, and require frequent re-calibration.
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Zhang, Z.: Camera Calibration. In: Medioni, G., Kang, S.B. (eds.) Emerging Topics in Computer Vision, ch. 2, pp. 4–43. Prentice Hall Professional Technical Reference (2004)
Zhang, Z.: Flexible Camera Calibration by Viewing a Plane from Unknown Orientations. In: ICCV 1999 (1999)
Bouguet, J.-Y.: Camera Calibration Toolbox for Matlab, http://www.vision.caltech.edu/bouguetj/calib_doc/index.html/
Abado, F., Camahort, E., Vivó, R.: Camera Calibration Using Two Concentric Circles. In: International Conference on Image Analysis and Recognition, pp. 688–696 (2004)
Ying, X., Zha, H.: Camera calibration using principal-axes aligned conics. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part I. LNCS, vol. 4843, pp. 138–148. Springer, Heidelberg (2007)
Yang, C., Sun, F., Hu, Z.: Planar conic based camera calibration. In: The 15th International Conference on Pattern Recognition, vol. 1, pp. 555–558 (2000)
Frosio, I., Alzati, A., Bertolini, M., Turrini, C., Borghese, N.A.: Linear pose estimate from corresponding conics. Pattern Recognition 45, 4169–4181 (2012)
Kahl, F., Heyden, A.: Using Conic Correspondences in Two Images to Estimate the Epipolar Geometry. In: Int. Conf. on Computer Vision, pp. 761–766 (1998)
Borghese, N.A., Colombo, F.M., Alzati, A.: Computing Camera Focal Length by Zooming a Single Point. Pattern Recognition 39, 1522–1529 (2006)
Faugeras, O.: Three-dimensional computer vision: a geometric viewpoint. MIT Press (1993)
Nikon website, http://www.nikon.com/
Canon website, http://www.canon.com/
Fraser, C.S., Ajlouni, A.S.S.: Zoom-dependent camera calibration in digital close-range photogrammetry. Photogrammetric Engineering & Remote Sensing 72(9), 1017–1026 (2006)
Sun, X., Sun, J., Zhang, J., Li, M.: Simple zoom-lens digital camera calibration method based on exif. In: Three-Dimensional Image Capture and Applications VI, vol. 79 (2004)
Calore, E., Frosio, I.: Perspective correction in digital photography using on board accelerometer. Submitted to Image and Vision Computing (2013)
Adi, B.-I., Greville, T.N.E.: Generalized inverses. Springer, New York (2003)
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Frosio, I., Turrini, C., Alzati, A. (2013). Conic Based Camera Re-calibration after Zooming. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41181-6_37
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DOI: https://doi.org/10.1007/978-3-642-41181-6_37
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