Abstract
In this paper, a new method is presented to use the epipolar constraint for the estimations of optical flows. We derive the necessary formulation to add the epipolar constraint in terms of optical flow components and force the components to transform points from the first frame to the next consecutive frame such that the points lie on their correspondent epipolar lines. In this work, no smoothness term is utilized and the performance of the proposed method is evaluated based only on data terms. We conducted different evaluations using two different point matching methods (SIFT and Lucas-Kanade) and used them in two different fundamental matrix estimation methods required to calculate epipolar line coefficients. It is demonstrated that epipolar constraint yields noticeable improvements almost in all of the cases.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kim, Y.H., Martinez, A.M., Kak, A.C.: Robust motion estimation under varying illumination. Image Vision Comput. 23, 365–375 (2005)
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)
Mueller, 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)
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)
Molnar, J., Chetverikov, D., Fazekas, S.: Illumination-robust variational optical flow using cross-correlation. Comput. Vis. Image Underst. 114, 1104–1114 (2010)
Werlberger, M., Pock, T., Bischof, H.: Motion estimation with non-local total variation regularization. In: CVPR, pp. 2464–2471. IEEE (2010)
Drulea, M., Nedevschi, S.: Motion estimation using the correlation transform. IEEE Trans. Image Process. 22, 3260–3270 (2013)
Rashwan, H.A., Mohamed, M.A., García, M.A., Mertsching, B., Puig, D.: Illumination robust optical flow model based on histogram of oriented gradients. In: Weickert, J., Hein, M., Schiele, B. (eds.) GCPR 2013. LNCS, vol. 8142, pp. 354–363. Springer, Heidelberg (2013)
Mohamed, M.A., Rashwan, H.A., Mertsching, B., Garcia, M.A., Puig, D.: Illumination-robust optical flow using local directional pattern. IEEE Trans. Circuits Syst. Video Technol. 24, 1–9 (2014)
Mohamed, M.A., Rashwan, H.A., Mertsching, B., Garcia, M.A., Puig, D.: On improving the robustness of variational optical flow against illumination changes. In: Proceedings of the 4th ACM/IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Stream, pp. 1–8. ACM (2013)
Hartley, R.I.: In defense of the eight-point algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 19, 580–593 (1997)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University, Cambridge (2004)
Yamaguchi, K., McAllester, D.A., Urtasun, R.: Robust monocular epipolar flow estimation. In: CVPR, pp. 1862–1869. IEEE (2013)
Lukas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Image Understanding Workshop (1981)
Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: the KITTI dataset. Int. J. Robot. Res. 32(11), 1231–1237 (2013)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Bouguet, J.Y.: Pyramidal implementation of the Lucas Kanade feature tracker. Intel Corporation, Microprocessor Research Labs (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mohamed, M.A., Mirabdollah, M.H., Mertsching, B. (2015). Differential Optical Flow Estimation Under Monocular Epipolar Line Constraint. In: Nalpantidis, L., Krüger, V., Eklundh, JO., Gasteratos, A. (eds) Computer Vision Systems. ICVS 2015. Lecture Notes in Computer Science(), vol 9163. Springer, Cham. https://doi.org/10.1007/978-3-319-20904-3_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-20904-3_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20903-6
Online ISBN: 978-3-319-20904-3
eBook Packages: Computer ScienceComputer Science (R0)