Abstract
We study the problem of estimating the position and orientation of a calibrated camera from an image of a known scene. A common problem in camera pose estimation is the existence of false correspondences between image features and modeled 3D points. Existing techniques such as ransac to handle outliers have no guarantee of optimality. In contrast, we work with a natural extension of the L ∞ norm to the outlier case. Using a simple result from classical geometry, we derive necessary conditions for L ∞ optimality and show how to use them in a branch and bound setting to find the optimum and to detect outliers. The algorithm has been evaluated on synthetic as well as real data showing good empirical performance. In addition, for cases with no outliers, we demonstrate shorter execution times than existing optimal algorithms.
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Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)
Atkinson, K.B.: Close Range Photogrammetry and Machine Vision. Whittles Publishing (1996)
Grunert, J.A.: Das pothenot’sche problem in erweiterter gestalt; nebst bemerkungen über seine anwendung in der geodäsie. Grunert Archiv der Mathematik und Physik 1(1841), 238–248
Olson, C.: A general method for geometric feature matching and model extraction. Int. Journal Computer Vision 45, 39–54 (2001)
Cass, T.: Polynomial-time geometric matching for object recognition. Int. Journal Computer Vision 21, 37–61 (1999)
Jacobs, D.: Matching 3-d models to 2-d images. Int. Journal Computer Vision 21, 123–153 (1999)
Huttenlocher, D., Ullman, S.: Object recognition using alignment. In: Int. Conf. Computer Vision, London, UK, pp. 102–111 (1987)
Jurie, F.: Solution of the simultaneous pose and correspondence problem using gaussian error model. Computer Vision and Image Understanding 73, 357–373 (1999)
Breuel, T.: Implementation techniques for geometric branch-and-bound matching methods. Computer Vision and Image Understanding 90, 258–294 (2003)
David, P., DeMenthon, D., Duraiswami, R., Samet, H.: SoftPOSIT: Simultaneous pose and correspondence determination. Int. Journal Computer Vision 59, 259–284 (2004)
Haralick, R.M., Lee, C.N., Ottenberg, K., Nolle, M.: Review and analysis of solutions of the 3-point perspective pose estimation problem. Int. Journal Computer Vision 13, 331–356 (1994)
Quan, L., Lan, Z.: Linear n ≤ 4-point camera pose determination. IEEE Trans. Pattern Analysis and Machine Intelligence 21, 774–780 (1999)
Hartley, R., Kahl, F.: Optimal algorithms in multiview geometry. In: Asian Conf. Computer Vision, Tokyo, Japan (2007)
Olsson, C., Kahl, F., Oskarsson, M.: Optimal estimation of perspective camera pose. In: Int. Conf. Pattern Recognition, Hong Kong, China, vol. II, pp. 5–8 (2006)
Hartley, R., Kahl, F.: Global optimization through searching rotation space and optimal estimation of the essential matrix. In: Int. Conf. Computer Vision, Rio de Janeiro, Brazil (2007)
Sim, K., Hartley, R.: Removing outliers using the L ∞ -norm. In: Conf. Computer Vision and Pattern Recognition, New York City, USA, pp. 485–492 (2006)
Li, H.: A practical algorithm for L ∞ triangulation with outliers. In: Conf. Computer Vision and Pattern Recognition, Minneapolis, USA (2007)
Olsson, C., Enqvist, O., Kahl, F.: A polynomial-time bound for matching and registration with outliers. In: CVPR 2008 (2008)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with application to image analysis and automated cartography. Commun. Assoc. Comp. Mach. 24, 381–395 (1981)
Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. Journal of the Optical Society of America A 4 (1987)
Snavely, N., Seitz, S., Szeliski, R.: Photo tourism: Exploring photo collections in 3d. ACM SIGGRAPH 25, 835–846 (2006)
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Enqvist, O., Kahl, F. (2008). Robust Optimal Pose Estimation. In: Forsyth, D., Torr, P., Zisserman, A. (eds) Computer Vision – ECCV 2008. ECCV 2008. Lecture Notes in Computer Science, vol 5302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88682-2_12
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DOI: https://doi.org/10.1007/978-3-540-88682-2_12
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