An evaluation of data costs for optical flow

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8142 LNCS, Issue , 2013, Pages 343-353

  Vogel, Christoph ^a   Roth, Stefan ^b   Schindler, Konrad ^a  

^a ETH ZURICH   (Switzerland)

^b DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC GAIN CONTROL; CAST SHADOW; DATA COSTS; OPTICAL FLOW ESTIMATION; REAL-WORLD; SYSTEMATIC EVALUATION;

GAIN CONTROL; MOTION ESTIMATION; OPTICAL FLOWS; PATTERN RECOGNITION;

COSTS;

EID: 84886408457     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40602-7_37     Document Type: Conference Paper

References (29)

1. Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.: A database and evaluation methodology for optical flow. In: ICCV (2007)
2. Barron, J., Fleet, D., Beauchemin, S.: Performance of optical flow techniques. IJCV (1994)
3. Black, M.J., Anandan, P.: A framework for the robust estimation of optical flow. In: ICCV (1993)
4. Bleyer, M., Rhemann, C., Rother, C.: PatchMatch Stereo - Stereo matching with slanted support windows. In: BMVC (2011)
5. Bredies, K., Kunisch, K., Pock, T.: Total generalized variation. SIAM J. Imaging Sciences 3(3), 492-526 (2010)
6. Brox, T., Bruhn, A., Papenberg, N.,Weickert, J.: High accuracy optical flow estimation based on a theory for warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25-36. Springer, Heidelberg (2004)
7. Bruhn, A., Weickert, J., Kohlberger, T., Schnörr, C.: A multigrid platform for real-time motion computation with discontinuity-preserving variational methods. IJCV 70(3) (2006)
8. Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. JMIV 40(1), 120-145 (2011)
9. Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? The KITTI vision benchmark suite. In: CVPR (2012)
10. Hafner, D., Demetz, O.,Weickert, J.:Why is the census transform good for robust optic flow computation? In: Kuijper, A., Bredies, K., Pock, T., Bischof, H. (eds.) SSVM 2013. LNCS, vol. 7893, pp. 210-221. Springer, Heidelberg (2013)
11. Haussecker, H.W., Fleet, D.J.: Computing optical flow with physical models of brightness variation. In: CVPR, vol. 2 (2000)
12. Hermann, S., Klette, R.: Hierarchical scan-line dynamic programming for optical flow using semi-global matching. In: Park, J.-I., Kim, J. (eds.) ACCV Workshops 2012, Part II. LNCS, vol. 7729, pp. 556-567. Springer, Heidelberg (2013)
13. Hirschmüller, H., Scharstein, D.: Evaluation of cost functions for stereo matching. In: CVPR (2007)
14. Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artif. Intell. 17(1-3) (1981)
15. Li,Y., Osher, S.: A new median formula with applications to PDE based denoising. Commun. Math. Sci. 7(3), 741-753 (2009)
16. Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: IJCAI (1981)
17. Müller, T., Rabe, C., Rannacher, J., Franke, U., Mester, R.: Illumination-robust dense optical flow using census signatures. In: Mester, R., Felsberg, M. (eds.) DAGM 2011. LNCS, vol. 6835, pp. 236-245. Springer, Heidelberg (2011)
18. Panin, G.: Mutual information for multi-modal, discontinuity-preserving image registration. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Fowlkes, C.,Wang, S., Choi,M.-H.,Mantler, S., Schulze, J., Acevedo, D., Mueller, K., Papka, M. (eds.) ISVC 2012, Part II. LNCS, vol. 7432, pp. 70-81. Springer, Heidelberg (2012)
19. Pock, T., Chambolle, A.: Diagonal preconditioning for first order primal-dual algorithms in convex optimization. In: ICCV (2011)
20. Ranftl, R., Gehrig, S., Pock, T., Bischof, H.: Pushing the limits of stereo using variational stereo estimation. In: Intelligent Vehicle Symposium (2012)
21. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena 60(1-4), 259-268 (1992)
22. Stein, F.: Efficient computation of optical flow using the census transform. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds.) DAGM 2004. LNCS, vol. 3175, pp. 79-86. Springer, Heidelberg (2004)
23. Steinbrücker, F., Pock, T., Cremers, D.: Advanced data terms for variational optic flow estimation. In: VMV (2009)
24. Sun, D., Roth, S., Black, M.J.: Secrets of optical flow estimation and their principles. In: CVPR (2010)
25. Viola, P., Wells III.W.: Alignment by maximization of mutual information. In: ICCV (1995)
26. Wedel, A., Pock, T., Zach, C., Bischof, H., Cremers, D.: An improved algorithm for TV-L1 optical flow. In: Cremers, D., Rosenhahn, B., Yuille, A.L., Schmidt, F.R. (eds.) Statistical and Geometrical Approaches to Visual Motion Analysis. LNCS, vol. 5604, pp. 23-45. Springer, Heidelberg (2009)
27. Werlberger, M., Pock, T., Bischof, H.: Motion estimation with non-local total variation regularization. In: CVPR (2010)
28. Zabih, R., Woodfill, J.: Non-parametric local transforms for computing visual correspondence. In: Eklundh, J.-O. (ed.) ECCV 1994. LNCS, vol. 801, pp. 151-158. Springer, Heidelberg (1994)
29. Zach, C., Pock, T., Bischof, H.: A duality based approach for realtime TV-L1 optical flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 214-223. Springer, Heidelberg (2007)