Local Affine Optical Flow Computation
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- 作者：Hayato Itoh (18)
Shun Inagaki (18)
Ming-Ying Fan (18)
Atsushi Imiya (19)
Kazuhiko Kawamoto (20)
Tomoya Sakai (21) - 刊名：Lecture Notes in Computer Science
- 出版年：2014
- 出版时间：2014
- 年：2014
- 卷：8334
- 期：1
- 页码：203-215
- 全文大小：4,452 KB
- 参考文献：1. Bouguet, J.-Y.: Pyramidal implementation of the Lucas Kanade feature tracker description of the algorithm, Intel Corporation, Microprocessor Research Labs, OpenCV Documents (1999)
2. Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: International Joint Conference on Artificial Intelligence, pp. 674鈥?79 (1981)
3. Beauchemin, S.S., Barron, J.L.: The computation of optical flow. ACM Computing Surveys聽27, 233鈥?66 (1995) CrossRef
4. van de Weijer, J., Gevers, T.: Robust optical flow from photometric invariants. In: Proc. ICIP, pp. 1835鈥?838 (2004)
5. Shi, J., Tomasi, C.: Good features to track. In: Proc. CVPR 1994, pp. 593鈥?00 (1994)
6. Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artificial Intelligence聽17, 185鈥?04 (1981) CrossRef
7. Bruckstein, A.M., Donoho, D.L., Elad, M.: From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Review聽51, 34鈥?1 (2009) CrossRef
8. Bruhn, A., Weickert, J., Schnoerr, C.: Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods. International Journal of Computer Vision Archive聽61, 211鈥?31 (2005)
9. Zach, C., Pock, T., Bischof, H.: A duality based approach for realtime TV- / L 1 optical flow. In: Hamprecht, F.A., Schn枚rr, C., J盲hne, B. (eds.) DAGM 2007. LNCS, vol.聽4713, pp. 214鈥?23. Springer, Heidelberg (2007) CrossRef
10. Papenberg, N., Bruhn, A., Brox, T., Didas, S., Weickert, J.: Highly accurate optic flow computation with theoretically justified warping 67, 141鈥?58 (2006)
11. Weickert, J., Schnoerr, C.: Variational optic flow computation with a spatio-temporal smoothness constraint. Journal of Mathematical Imaging and Vision聽14, 245鈥?55 (2001) CrossRef
12. Shin, Y.-Y., Chang, O.-S., Xu, J.: Convergence of fixed point iteration for deblurring and denoising problem. Applied Mathematics and Computation聽189, 1178鈥?185 (2007) CrossRef
13. Chambolle, A.: An algorithm for total variation minimization and applications. Journal of Mathematical Imaging and Vision聽20, 89鈥?7 (2004) CrossRef - 作者单位：Hayato Itoh (18)
Shun Inagaki (18)
Ming-Ying Fan (18)
Atsushi Imiya (19)
Kazuhiko Kawamoto (20)
Tomoya Sakai (21)
18. School of Advanced Integration Science, Chiba University, Japan
19. Institute of Management and Information Technologies, Chiba University, Japan
20. Academic Link Center, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba, 263-8522, Japan
21. Department of Computer and Information Sciences, Nagasaki University, Bunkyo-cho, Nagasaki, 852-8521, Japan - ISSN：1611-3349
文摘
We develop an algorithm for the computation of a locally affine optical flow field as an extension of the Lucas-Kanade (LK) method. The classical LK method solves a system of linear equations assuming that the flow field is locally constant. Our method solves a collection of systems of linear equations assuming that the flow field is locally affine. Since our method combines the minimisation of the total variation and the decomposition of the region, the method is a local version of the $l_2^2$ -l 1 optical flow computation. Since the linearly diverging vector field from a point is locally affine, our method is suitable for optical flow computation for diverging image sequences such as front-view sequences observed by car-mounted cameras.