DOI: 10.1007/978-3-540-69321-5_32. A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow

A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow

10.1007/978-3-540-69321-5_32

Crossref book-chapter

Springer Berlin Heidelberg

Lecture Notes in Computer Science (297)

Bibliography

Valgaerts, L., Bruhn, A., & Weickert, J. (n.d.). A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow. Pattern Recognition, 314â324.

Authors 3

Levi Valgaerts (first)
Andrés Bruhn (additional)
Joachim Weickert (additional)

References 19 Referenced 24

Amiaz, T., Lubetzky, E., Kiryati, N.: Coarse to over-fine optical flow estimation. Pattern Recognition 40(9), 2496–2503 (2007) (10.1016/j.patcog.2006.09.011) / Pattern Recognition by T. Amiaz (2007)
Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994) (10.1007/BF01420984) / International Journal of Computer Vision by J.L. Barron (1994)
Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High accuracy optic flow estimation based on a theory for warping. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25–36. Springer, Berlin (2004) (10.1007/978-3-540-24673-2_3) / Computer Vision - ECCV 2004 / Lecture Notes in Computer Science by T. Brox (2004)
Bruhn, A., Weickert, J., Schnörr, C.: Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods. International Journal of Computer Vision 61(3), 211–231 (2005) (10.1023/B:VISI.0000045324.43199.43) / International Journal of Computer Vision by A. Bruhn (2005)
Faugeras, O., Luong, Q.-T., Papadopoulo, T.: The Geometry of Multiple Images. MIT Press, Cambridge (2001) (10.7551/mitpress/3259.001.0001) / The Geometry of Multiple Images by O. Faugeras (2001)
Fischler, M., Bolles, R.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–385 (1981) (10.1145/358669.358692) / Communications of the ACM by M. Fischler (1981)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000) / Multiple View Geometry in Computer Vision by R. Hartley (2000)
Hartley, R.I.: In defense of the eight-point algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(6), 580–593 (1997) (10.1109/34.601246) / IEEE Transactions on Pattern Analysis and Machine Intelligence by R.I. Hartley (1997)
Huber, P.J.: Robust Statistics. Wiley, New York (1981) (10.1002/0471725250) / Robust Statistics by P.J. Huber (1981)
Longuet-Higgins, H.C.: A computer algorithm for reconstructing a scene from two projections. Nature 293, 133–135 (1981) (10.1038/293133a0) / Nature by H.C. Longuet-Higgins (1981)
Luong, Q.-T., Faugeras, O.D.: The fundamental matrix: theory, algorithms, and stability analysis. International Journal of Computer Vision 17(1), 43–75 (1996) (10.1007/BF00127818) / International Journal of Computer Vision by Q.-T. Luong (1996)
Mainberger, M., Bruhn, A., Weickert, J.: Is dense optical flow useful to compute the fundamental matrix? In: Campilho, A., Kamel, M. (eds.) Image Analysis and Recognition. LNCS, Springer, Berlin (to appear, 2008) (10.1007/978-3-540-70540-6) / Image Analysis and Recognition / Lecture Notes in Computer Science by M. Mainberger (2008)
Mémin, E., Pérez, P.: Hierarchical estimation and segmentation of dense motion fields. International Journal of Computer Vision 46(2), 129–155 (2002) (10.1023/A:1013539930159) / International Journal of Computer Vision by E. Mémin (2002)
Nir, T., Bruckstein, A.M., Kimmel, R.: Over-parameterized variational optical flow. International Journal of Computer Vision 76(2), 205–216 (2008) (10.1007/s11263-007-0051-2) / International Journal of Computer Vision by T. Nir (2008)
Roth, S., Black, M.: On the spatial statistices of optical flow. In: Proc. Tenth International Conference on Computer Vision, Beijing, China, June 2005, pp. 42–49. IEEE Computer Society Press, Los Alamitos (2005) / Proc. Tenth International Conference on Computer Vision by S. Roth (2005)
Rousseeuw, P.J., Leroy, A.M.: Robust Regression and Outlier Detection. Wiley, New York (1987) (10.1002/0471725382) / Robust Regression and Outlier Detection by P.J. Rousseeuw (1987)
Saragih, J., Goecke, R.: Monocular and stereo methods for AAM learning from Video. In: Proc. 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, June 2007, pp. 1–7. IEEE Computer Society Press, Los Alamitos (2007) / Proc. 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition by J. Saragih (2007)
Sheikh, Y., Hakeem, A., Shah, M.: On the direct estimation of the fundamental matrix. In: Proc. 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, June 2007, pp. 1–7. IEEE Computer Society Press, Los Alamitos (2007) / Proc. 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition by Y. Sheikh (2007)
Slesareva, N., Bruhn, A., Weickert, J.: Optic flow goes stereo: a variational approach for estimating discontinuity-preserving dense dispartiy maps. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds.) DAGM 2005. LNCS, vol. 3663, pp. 33–40. Springer, Berlin (2005) (10.1007/11550518_5) / Pattern Recognition / Lecture Notes in Computer Science by N. Slesareva (2005)

Dates

Type	When
Created	17 years, 1 month ago (July 30, 2008, 10:38 p.m.)
Deposited	4 years, 3 months ago (May 2, 2021, 8:36 p.m.)
Indexed	5 months, 1 week ago (March 24, 2025, 2:59 a.m.)

Funders 0

None

BibTeX

@inbook{Valgaerts, title={A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow}, ISBN={9783540693215}, ISSN={1611-3349}, url={http://dx.doi.org/10.1007/978-3-540-69321-5_32}, DOI={10.1007/978-3-540-69321-5_32}, booktitle={Pattern Recognition}, publisher={Springer Berlin Heidelberg}, author={Valgaerts, Levi and Bruhn, Andrés and Weickert, Joachim}, pages={314–324} }

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