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Line geometry and camera autocalibration

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2008-10
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Springer
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We provide a completely new rigorous matrix formulation of the absolute quadratic complex (AQC), given by the set of lines intersecting the absolute conic. The new results include closed-form expressions for the camera intrinsic parameters in terms of the AQC, an algorithm to obtain the dual absolute quadric from the AQC using straightforward matrix operations, and an equally direct computation of a Euclidean-upgrading homography from the AQC. We also completely characterize the 6x6 matrices acting on lines which are induced by a spatial homography. Several algorithmic possibilities arising from the AQC are systematically explored and analyzed in terms of efficiency and computational cost. Experiments include 3D reconstruction from real images.
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Agapito, L., Hayman, E., Reid, I.: Self-calibration of rotating and zooming cameras. Int. J. Comput. Vis. 45, 107–127 (2001) Bartoli, A., Sturm, P.: The 3d line motion matrix and alignment of line reconstructions. Int. J. Comput. Vis. 57, 159–178 (2004) Bayro-Corrochano, E., Banarer, V.: A geometric approach for the theory and applications of 3d projective invariants. J. Math. Imaging Vis. 16(2), 131–154 (2002) Berger, M.: Geometry. Springer, Berlin (1987) Bougnoux, S.: From projective to euclidean space under any practical situation, a criticism of self-calibration. In: Proc. International Conference on Computer Vision, Brisbane, Australia, pp. 790–796 (1998) Carlsson, S.: The double algebra: An effective tool for computing invariants in computer vision. In: Proc. of the Second Joint European-US Workshop on Applications of Invariance in Computer Vision, London, UK, 1994, pp. 145–164. Springer, Berlin (1994) Faugeras, O.: What can be seen in three dimensions with an uncalibrated stereo rig. In: Proc. European Conference on Computer Vision, pp. 563–578 (1992) Faugeras, O.: Three Dimensional Computer Vision. MIT Press, Cambridge (1993) Faugeras, O., Luong, Q.-T., Papadopoulou, T.: The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications. MIT Press, Cambridge (2001) Forsyth, D.A., Ponce, J.: Computer Vision: A Modern Approach. Prentice Hall, New York (2002) Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003) Hartley, R.I.: Estimation of relative camera positions for uncalibrated cameras. In: Proc. European Conference on Computer Vision, London, UK, 1992, pp. 579–587. Springer, Berlin (1992) Heyden, A.: Geometry and algebra of multiple projective transformations. PhD thesis, Lund University (1995) Heyden, A., Åström, K.: Euclidean reconstruction from image sequences with varying and unknown focal length and principal point. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, New York, USA (1997) Kahl, F., Triggs, B., Åström, K.: Critical motions for autocalibration when some intrinsic parameters can vary. J. Math. Imaging Vis. 13(2), 131–146 (2000) Ma, Y., Soatto, S., Kosecka, J., Sastry, S.: An Invitation to 3-D Vision. Springer, Berlin (2005) Maybank, S.J., Faugeras, O.D.: A theory of self-calibration of a moving camera. Int. J. Comput. Vis. 8(2), 123–151 (1992) Pollefeys, M., Gool, L.V.: A stratified approach to metric selfcalibration. In: Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 407–412 (1997) Pollefeys, M., Koch, R., van Gool, L.: Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters. Int. J. Comput. Vis. 1(32), 7–25 (1999) Ponce, J.: On computing metric upgrades of projective reconstructions under the rectangular pixel assumption. In: Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments, London, UK, 2001, pp. 52–67. Springer, Berlin (2001) Ponce, J., McHenry, K., Papadopoulo, T., Teillaud, M., Triggs, B.: On the absolute quadratic complex and its application to autocalibration. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, vol. 1, pp. 780–787 (2005) Pottman, H.,Wallner, J.: Computational Line Geometry. Springer, New York (2001) Press,W.H., Teukolsky, S.A., Vetterling,W.T., Flannery, B.P.: Numerical Recipes in C: The Art of Scientific Computing, 2nd edn. Cambridge University Press, Cambridge (1993) Ronda, J.I., Gallego, G., Valdés, A.: Camera autocalibration using Plücker coordinates. In: International Conference on Image Processing, Genoa, Italy, vol. 3, pp. 800–803 (2005) Semple, J.G., Kneebone, G.T.: Algebraic Projective Geometry. Oxford Classic Texts in the Physical Sciences. Clarendon, Oxford (1952) Seo, Y., Heyden, A.: Auto-calibration from the orthogonality constraints. In: Proc. International Conference on Pattern Recognition, Los Alamitos, CA, USA, vol. 01, pp. 1067–1071 (2000) Seo, Y., Heyden, A., Cipolla, R.: A linear iterative method for auto-calibration using the dac equation. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, Barcelona, Spain, pp. 880–885 (2001) Trefethen, L.N., Bau, D.: Numerical Linear Algebra. SIAM, Philadelphia (1997) Triggs, B.: Autocalibration and the absolute quadric. In: Proc. Of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, USA, June 1997, pp. 609–614 (1997) Valdés, A., Ronda, J.: Camera autocalibration and the calibration pencil. J. Math. Imaging Vis. 23(2), 167–174 (2005) Valdés, A., Ronda, J.I., Gallego, G.: Linear camera autocalibration with varying parameters. In: Proc. International Conference on Image Processing, Singapore, vol. 5, pp. 3395–3398 (2004) Valdés, A., Ronda, J.I., Gallego, G.: The absolute line quadric and camera autocalibration. Int. J. Comput. Vis. 66(3), 283–303 (2006)
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