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Paraperspective ≡ affine

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Abstract

It is shown that the set of all paraperspective images with arbitrary reference point and the set of all affine images of a 3-D object are identical. Consequently, all uncalibrated paraperspective images of an object can be constructed from a 3-D model of the object by applying an affine transformation to the model, and every affine image of the object represents some uncalibrated paraperspective image of the object. It follows that the paraperspective images of an object can be expressed as linear combinations of any two non-degenerate images of the object. When the image position of the reference point is given the parameters of the affine transformation (and, likewise, the coefficients of the linear combinations) satisfy two quadratic constraints. Conversely, when the values of parameters are given the image position of the reference point is determined by solving a bi-quadratic equation.

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References

  • Aloimonos, J. 1990. Perspective approximations. Image and Vision Computing, 8(3):177–192.

    Google Scholar 

  • Basri, R. 1993. Viewer-centered representations in object recognition: A computational approach. In: C.H., Chen, L.F., Pau, and P.S.P., Wang (Eds.), Handbook of Pattern Recognition and Computer Vision, World Scientific Publishing Company: Singapore, Chapter 5.4, pp. 863–882.

    Google Scholar 

  • Faugeras, O.D. 1992. What can be seen in three dimensions with an uncalibrated stereo rig? European Conf. on Computer Vision (ECCV-92), pp. 564–578.

  • Jacobs, D. 1994. Matching 3-D models to 2-D images. International Journal of Computer Vision, forthcoming.

  • Koenderink, J. and van, Doorn, A. 1991. Affine structure from motion. Journal of the Optical Society of America, 8(2):377–385.

    Google Scholar 

  • Longuet-Higgins, H.C. 1981. A computer algorithm for reconstructing a scene from two projections. Nature, 293:133–135.

    Google Scholar 

  • Ohta, Y., Maenobu, K., and Sakai, T. 1981. Obtaining surface orientation from textels under perspective projection. Proc. of the 7th International Joint Conference on Artificial Intelligence, pp. 746–751.

  • Poelman, C.J. and Kanade, T. 1994. A paraperspective factorization method for shape and motion recovery. European Conf. on Computer Vision (ECCV-94).

  • Poggio, T. 1990. 3D object recognition: On a result by Basri and Ullman. TR 9005–03, IRST, Povo, Italy.

    Google Scholar 

  • Sugimoto, A. 1995. Object recognition by combining paraperspective images. International Journal of Computer Vision, forthcoming.

  • Sugimoto, A. and Murota, K. 1993. 3D object recognition by combination of perspective images. Proc. of SPIE, 1904:183–195.

    Google Scholar 

  • Tsai, R.Y. and Huang, T.S. 1984. Uniqueness and estimation of three-dimensional motion parameters of rigid objects with curved surfaces. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6(1):13–27.

    Google Scholar 

  • Ullman, S. and Basri, R. 1991. Recognition by linear combinations of models. IEEE Trans. on Pattern Analysis and Machine Intelligence, 13(10):992–1006.

    Google Scholar 

  • Weinshall, D. and Tomasi, C. 1992. Linear and incremental acquisition of invariant shape models from image sequences. International Journal of Computer Vision, forthcoming.

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Basri, R. Paraperspective ≡ affine. Int J Comput Vision 19, 169–179 (1996). https://doi.org/10.1007/BF00055803

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  • DOI: https://doi.org/10.1007/BF00055803

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