Abstract
The computation for image mosaicing using homographies is numerically unstable and causes large image distortions if the matching points are small in number and concentrated in a small region in each image. This instability stems from the fact that actual transformations of images are usually in a small subgroup of the group of homographies. It is shown that such undesirable distortions can be removed by model selection using the geometric AIC without introducing any empirical thresholds. It is shown that the accuracy of image mosaicing can be improved beyond the theoretical bound imposed on statistical optimization. This is made possible by our knowledge about probable subgroups of the group of homographies.We demonstrate the effectiveness of our method by real image examples.
Acknowledgments
This work was in part supported by the Ministry of Education, Science, Sports and Culture, Japan under a Grant in Aid for Scientific Research C(2) (No. 11680377).
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References
H. Akaike,A newlook at the statistical model identification, IEEE Trans. Automation Control, 19-6 (1974), 716–723.
W. Förstner, Reliability analysis of parameter estimation in linear models with applications to mensuration problems in computer vision, Comput. Vision Graphics Image Process., 40 (1987), 273–310.
K. Kanatani, Geometric Computation for Machine Vision, Oxford University Press, Oxford, 1993.
K. Kanatani, Statistical Optimization for Geometric Computation: Theory and Practice, Elsevier Science, Amsterdam, 1996.
K. Kanatani, Geometric information criterion for model selection, Int. J. Comput. Vision, 26-3 (1998), 171–189.
K. Kanatani, Statistical optimization and geometric inference in computer vision, Phil. Trans. Roy. Soc. Lond., A-356 (1998), 1303–1320.
K. Kanatani and N. Ohta, Accuracy bounds and optimal computation of homography for image mosaicing applications, Proc. 7th Int. Conf. Comput. Vision, September, 1999, Kerkya, Greece, pp. 73–78.
C. Matsunaga and K. Kanatani, Calibration of a moving camera using a planar pattern: Optimal computation, reliability evaluation and stabilization by model selection, Proc. 6th Euro. Conf. Comput. Vision, June-July 2000, Dublin, Ireland, Vol.2, pp. 595–609.
D. D. Morris and T. Kanade, A unified factorization algorithm for points, line segments and planes with uncertainty models, Proc. Int. Conf. Comput. Vision, January 1998, Bombay, India, pp. 696–702.
H. S. Sawhney, S. Hsu and R. Kumar, Robust video mosaicing through topology inference and local to global alignment, Proc. 5th Euro. Conf. Comput. Vision, June 1998, Freiburg, Germany, Vol. 2, pp. 103–119.
J. Shi and C. Tomasi, Good features to track, Proc. Conf. Comput. Vision Patt. Recogn., June 1994, Seattle,WA, pp. 593–600.
A. Singh,An estimation-theoretic framework for image-flowcomputation, Proc. 3rd Int. Conf. Comput. Vision, December, dy1990, Osaka, Japan, pp. 168–177.
R. Szeliski and H.-U. Shum, Creating full view panoramic image mosaics and environment maps, Proc. SIGGRAPH’97, August 1997, Los Angeles, CA, U.S.A., pp. 251–258.
P. H. S. Torr, Model selection for two view geometry:A review, in, D. A. Forsyth, J. L. Mundy, V. D. Gesú, R. Cipolla (Eds.): Shape, Contour and Grouping in ComputerVision, LNCS 1681, Springer-Verlag, Berlin, 1999, pp. 277–301.
T. Werner, T. Pajdla and V. Hlaváč, Efficient 3-D scene visualization by image extrapolation, Proc. 5th Euro. Conf. Comput. Vision, June 1998, Freiburg, Germany, Vol. 2, pp. 382–396.
I. Zoghlami, O. Faugeras and R. Deriche, Using geometric corners to build a 2D mosaic from a set of images, Proc. Conf. Comput. Vision Patt. Recogn., June 1997, Puerto Rico, pp. 420–425.
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Kanazawa, Y., Kanatani, K. (2001). Stabilizing Image Mosaicing by Model Selection. In: Pollefeys, M., Van Gool, L., Zisserman, A., Fitzgibbon, A. (eds) 3D Structure from Images — SMILE 2000. SMILE 2000. Lecture Notes in Computer Science, vol 2018. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45296-6_3
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DOI: https://doi.org/10.1007/3-540-45296-6_3
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