Abstract
This paper describes a method for generating a three-dimensional model from an uncalibrated image sequence taken around an object. Our method is based on feature tracking and minimization of re-projection errors. To cope with mis-matchings in the result of feature tracking, we introduce two types of global geometric constraints. The one is “affine constraint” which imposes the positional relationship between pixels on the images. The other is “depth constraint” which imposes the three-dimensional structure of the object. First, we use the affine constraint to reconstruct the object roughly and then we refine the feature tracking and shape reconstruction using the depth constraint. Experimental results show that our method can automatically generate accurate three-dimensional models from real image sequences.
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References
Matthies, L., Kanade, T., Szeliski, R.: Kalman filter-based algorithms for estimating depth from image sequences. International Journal of Computer Vision 3, 209–239 (1989)
Gimel’farb, G.L., Haralick, R.M.: Terrain reconstruction from multiple views. In: Sommer, G., Daniilidis, K., Pauli, J. (eds.) CAIP 1997. LNCS, vol. 1296, pp. 694–701. Springer, Heidelberg (1997)
Beardsley, P., Torr, P., Zisserman, A.: 3D Model Acquisition from Extended Image Sequences. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1065, pp. 683–695. Springer, Heidelberg (1996)
Koch, R., Pollefeys, M., Gool, L.V.: Multi Viewpoint Stereo from Uncalibrated Video Sequences. In: Burkhardt, H.-J., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 55–71. Springer, Heidelberg (1998)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)
Harris, C., Stephens, M.: A Combined Corner and Edge Detector. In: Proc. Alvey Vision Conf., pp. 147–151 (1988)
Szeliski, R., Kang, S.B.: Recovering 3D Shape and Motion from Image Streams using Non-Linear Least Squares. In: CVPR, pp. 752–753 (1993)
Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle Adjustment – A Modern Synthesis. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) ICCV-WS 1999. LNCS, vol. 1883, pp. 298–375. Springer, Heidelberg (2000)
Amano, A., Migita, T., Asada, N.: Stable Recovery of Shape and Motion from Partially Tracked Feature Points with Fast Nonlinear Optimization. In: Proc. on Vision Interface, pp. 244–251 (2002)
Asada, N., Mukunoki, M., Migita, T., Aoyama, M.: Large Object Shape Recovery from Uncalibrated Camera Motion by Non-Linear Optimization. In: Proc. Int. Conf. on Signal and Image Processing, pp. 151–156 (2004)
Zhang, Z.: Determining The Epipolar Geometry And Its Uncertainty: A Review. IJCV 27, 161–195 (1998)
Zhang, Z., Deriche, R., Faugeras, O., Luong, Q.-T.: A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. In: Proc. 3rd Artif. Intell., vol. 78, pp. 87–119 (1995)
Kanazawa, Y., Kanatani, K.: Robust Image Matching Preserving Global Consistency. In: Proc. 6th ACCV, pp. 1128–1133 (2004)
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Mukunoki, M., Yasuda, K., Asada, N. (2005). 3D Model Generation from Image Sequences Using Global Geometric Constraint. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_57
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DOI: https://doi.org/10.1007/11595755_57
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