Abstract
While estimating both components of optical flow based on the postulated validity of the Optical Flow Constraint Equation (OFCE), it has been tacitly assumed so far that the partial derivatives of the gray value distribution — which are required for this approach at the pixel positions involved — are independent from each other. [Nagel 94] has shown in a theoretical investigation how dropping this assumption affects the estimation procedure. The advantage of such a more rigorous approach consists in the possibility to replace heuristic tests for the local detection of discontinuities in optical flow fields by well known stochastic tests. First results from various experiments with this new approach are presented and discussed.
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References
Barron, J.L., Fleet, D.J., Beauchemin, S.S., and Burkitt, T.A.: Performance of Optical Flow Techniques. In Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR '92, 15–18 June 1992, Champaign, IL, pp. 236–242. See, too, Int. Journal of Computer Vision 12:1 (1994) 43–77.
Bouthemy, P., and Santillana Rivero, J.: A Hierarchical Likelihood Approach for Region Segmentation According to Motion-Based Criteria. In Proc. First Intern. Conference on Computer Vision ICCV '87, London, UK, 8–11 June 1987, pp. 463–467.
Bouthemy, P., and Francois, E.: Motion Segmentation and Qualitative Scene Analysis from an Image Sequence. Int. Journal of Computer Vision 10:2 (1993) 157–182
Burt, P. J., Hingorani, R., and Kolczynski, R.: Mechanisms for Isolation Component Patterns in the Sequential Analysis of Multiple Motion. In Proc. IEEE Workshop on Visual Motion, Princeton, NJ, 7–9 October 1991, pp. 187–193.
Campani, M., and Verri, A.: Motion Analysis from First Order Properties of Optical Flow. CVGIP: Image Understanding 56:1 (1992) 90–107.
Chou, W.-S., and Chen, Y.-C.: Estimation of the Velocity Field of Two-Dimensional Deformable Motion. Pattern Recognition 26:2 (1993) 351–364.
De Micheli, E., Torre, V., and Uras, S.: The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-15:5 (1993) 434–447.
Etoh, M., and Shirai, Y.: Segmentation and 2D Motion Estimation by Region Fragments. In Proc. Fourth Intern. Conference on Computer Vision ICCV '93, 11–14 May 1993, Berlin, Germany, pp. 192–199.
Fleet, D.J.: Measurement of Image Velocity. Kluwer Academic Publishers: Boston, MA; London, UK; Dordrecht, NL, 1992
H. Gu, M. Asada, and Y. Shirai: The Optimal Partition of Moving Edge Segments. In Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR '93, 15–17 June 1993, New York City, NY, pp. 367–372.
Horn, B.K.P.: Robot Vision. The MIT Press: Cambridge, MA, 1986
Irani, M., Rousso, B., and Peleg, S.: Detecting and Tracking Multiple Moving Objects Using Temporal Integration. In Proc. Second European Conference on Computer Vision ECCV '92, Santa Margherita Ligure, Italy, 18–23 May 1992, Lecture Notes in Computer Science 588, G. Sandini (ed.), Springer-Verlag: Berlin Heidelberg New York and others, pp. 282–287.
H. Kollnig, H.-H. Nagel, and M. Otte: Association of Motion Verbs with Vehicle Movements Extracted from Dense Optical Flow Fields. Proc. ECCV '94, Stockholm / Sweden, 2–6 May 1994.
Letang, J.M., Rebuffel, V., and Bouthemy, P.: Motion Detection Robust to Perturbations: a Statistical Regularization and Temporal Integration Framework. In Proc. Fourth Intern. Conference on Computer Vision ICCV '93, 11–14 May 1993, Berlin, Germany, pp. 21–30.
Nagel, H.-H.: Direct Estimation of Optical Flow and of Its Derivatives. In Artificial and Biological Vision Systems, G. Orban and H.-H. Nagel (eds.). Springer-Verlag: Berlin Heidelberg New York and others, 1992, pp. 193–224.
Nagel, H.-H.: Optical Flow Estimation and the Interaction Between Measurement Errors at Adjacent Pixel Positions. Int. Journal of Computer Vision, to appear 1994.
Negahdaripour, S., and Lee, S.: Motion Recovery from Image Sequences Using Only First Order Optical Flow Information. Int. Journal of Computer Vision 9:3 (1992) 163–184.
Negahdaripour, S., and Yu, C.-H.: A Generalized Brightness Change Model for Computing Optical Flow. In Proc. Fourth Intern. Conference on Computer Vision ICCV '93, 11–14 May 1993, Berlin, Germany, pp. 2–11.
M. Otte and H.-H. Nagel: Optical Flow Estimation: Advances and Comparisons. Proc. ECCV '94, Stockholm / Sweden, 2–6 May 1994.
Simoncelli, E.P., Adelson, E.H., and Heeger, D.J.: Probability Distributions of Optical Flow. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, Lahaina, Maui, Hawaii, 3–6 June 1991, pp. 310–315.
Spoerri, A., and Ullman, S.: The Early Detection of Motion Boundaries. In Proc. First Intern. Conference on Computer Vision ICCV '87, London, UK, 8–11 June 1987, pp. 209–218.
Szeliski, R.: Bayesian Modeling of Uncertainty in Low-level Vision. Kluwer Academic Publishers: Boston, MA; Dordrecht, NL; London, UK, 1989
Szeliski, R.: Bayesian Modeling of Uncertainty in Low-Level Vision. Int. Journal of Computer Vision 5:3 (1990) 271–301.
Thompson, W.B., and Pong, T.-C.: Detecting Moving Objects. Intern. Journal of Computer Vision 4:1 (1990) 39–57.
Torr, P.H.S., and Murray, D.W.: Statistical Detection of Independent Movement from a Moving Camera. In Proc. British Machine Vision Conference, Leeds, UK, 22–24 Sept. 1992, D. Hogg and R. Boyle (eds.), Springer-Verlag: London Berlin Heidelberg and others, pp. 79–88. See, too, Image and Vision Computing 11:4 (1993) 180–187.
Wang, J.Y.A., and Adelson, E.H.: Layered Representation for Motion Analysis. In Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR '93, 15–17 June 1993, New York City, NY, pp. 361–366.
Weber, J., and Malik, J.: Robust Computation of Optical Flow in a Multiscale Differential Framework. In Proc. Fourth Intern. Conference on Computer Vision ICCV '93, 11–14 May 1993, Berlin, Germany, pp. 12–20.
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© 1994 Springer-Verlag Berlin Heidelberg
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Nagel, H.H., Socher, G., Kollnig, H., Otte, M. (1994). Motion boundary detection in image sequences by local stochastic tests. In: Eklundh, JO. (eds) Computer Vision — ECCV '94. ECCV 1994. Lecture Notes in Computer Science, vol 801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028363
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DOI: https://doi.org/10.1007/BFb0028363
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