An improved algorithm for TV-L1 optical flow

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

Volumn 5604 LNCS, Issue , 2009, Pages 23-45

  Wedel, Andreas ^a,c   Pock, Thomas ^b   Zach, Christopher ^d   Bischof, Horst ^b   Cremers, Daniel ^a  

^a UNIVERSITY OF BONN   (Germany)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^c DAIMLER AG   (Germany)

^d Brooks Computer Science Building   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA FIDELITY; ILLUMINATION CHANGES; IMAGE DATA; IMAGE FRAMES; INPUT IMAGE; NUMERICAL SCHEME; OPTICAL FLOW ALGORITHM; ROBUST ESTIMATION; TOTAL VARIATION REGULARIZATION; VARIATIONAL APPROACHES; VARIATIONAL METHODS;

NUMERICAL METHODS; VISION;

OPTICAL FLOWS;

EID: 84872260013     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03061-1_2     Document Type: Conference Paper

References (31)

1. Alvarez, L., Weickert, J., Sánchez, J.: A scale-space approach to nonlocal optical flow calculations. In: Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision, pp. 235-246 (1999)
2. Anandan, P.: A computational framework and an algorithm for the measurement of visual motion. Int. J. Comput. Vision 2, 283-310 (1989)
3. Aubert, G., Deriche, R., Kornprobst, P.: Computing optical flow via variational techniques. SIAM J. Appl. Math. 60(1), 156-182 (1999)
4. Aujol, J.-F., Gilboa, G., Chan, T., Osher, S.: Structure-texture image decomposition-modeling, algorithms, and parameter selection. Int. J. Comput. Vision 67(1), 111-136 (2006)
5. Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.: A Database and Evaluation Methodology for Optical Flow. In: ICCV 1993, pp. 1-8 (2007)
6. Birchfield, S.: Derivation of Kanade-Lucas-Tomasi Tracking Equation. Technical Report (1997)
7. Black, M.J., Anandan, P.: A framework for the robust estimation of optical flow. In: ICCV 1993, pp. 231-236 (1993)
8. Bresson, X., Esedoglu, S., Vandergheynst, P., Thiran, J., Osher, S.: Fast Global Minimization of the Active Contour/Snake Model. Journal of Mathematical Imaging and Vision (2007)
9. 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)
10. Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnörr, C.: Variational optical flow computation in real time. IEEE Transactions on Image Processing 14(5), 608-615 (2005)
11. Bruhn, A., Weickert, J., Kohlberger, T., Schnörr, C.: A multigrid platform for real-time motion computation with discontinuity-preserving variational methods. Int. J. Comput. Vision 70(3), 257-277 (2006)
12. Camus, T.A.: Real-time quantized optical flow. Journal of Real-Time Imaging 3, 71-86 (1997); Special Issue on Real-Time Motion Analysis
13. Chambolle, A.: An algorithm for total variation minimization and applications. Journal of Mathematical Imaging and Vision 20(1-2), 89-97 (2004)
14. Chambolle, A.: Total variation minimization and a class of binary MRF models. Energy Minimization Methods in Computer Vision and Pattern Recognition, 136-152 (2005)
15. Chan, T.F., Golub, G.H., Mulet, P.: A nonlinear primal-dual method for total variation-based image restoration. In: ICAOS 1996, Paris, vol. 219, pp. 241-252 (1996)
16. Devillard, N.: Fast median search: an ANSI C implementation (1998), http://www.eso.org/ndevilla/median/ (visited October 2008)
17. Haussecker, H., Fleet, D.J.: Estimating Optical Flow with Physical Models of Brightness Variation. IEEE Transactions on Pattern Analysis andMachine Intelligence 23(6), 661-674 (2001)
18. Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artificial Intelligence 17, 185-203 (1981)
19. Mémin, E., Pérez, P.: Hierarchical estimation and segmentation of dense motion fields. Int. J. Comput. Vision 46(2), 129-155 (2002)
20. Mileva, Y., Bruhn, A., Weickert, J.: Illumination-robust Variational Optical Flow with Photometric Invariants. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 152-162. Springer, Heidelberg (2007)
21. Nagel, H.-H., Enkelmann, W.: An investigation of smoothness constraints for the estimation of displacement vector fields from image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 8, 565-593 (1986)
22. Papenberg, N., Bruhn, A., Brox, T., Didas, S., Weickert, J.: Highly accurate optic flow computation with theoretically justified warping. Int. J. Comput. Vision, 141-158 (2006)
23. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D 60, 259-268 (1992)
24. Stewart, E.: Intel Integrated Performance Primitives: How to Optimize Software Applications Using Intel IPP. Intel Press (2004) ISBN 0971786135
25. Strzodka, R., Garbe, C.: Real-time motion estimation and visualization on graphics cards. In: IEEE Visualization 2004, pp. 545-552 (2004)
26. Trobin, W., Pock, T., Cremers, D., Bischof, H.: An Unbiased Second-Order Prior for High-Accuracy Motion Estimation. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 396-405. Springer, Heidelberg (2008)
27. Wedel, A., Pock, T., Braun, J., Franke, U., Cremers, D.: Duality TV-L1 flow with fundamental matrix prior. Image and Vision Computing New Zealand (November 2008)
28. Wedel, A., Rabe, C., Vaudrey, T., Brox, T., Franke, U., Cremers, D.: Efficient Dense Scene Flow from Sparse or Dense Stereo Data. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 739-751. Springer, Heidelberg (2008)
29. Weickert, J., Brox, T.: Diffusion and regularization of vector- and matrix-valued images. Inverse Problems, Image Analysis and Medical Imaging. Contemporary Mathematics 313, 251-268 (2002)
30. van de Weijer, J., Gevers, T.: Robust Pptical Flow from Photometric Invariants. In: International Conference on Image Processing (2004)
31. 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)