A High-Performance Dense Optical Flow Architecture Based on Red-Black SOR Solver

Author:

Johnson BibinORCID,Thomas Sachin,Sheeba Rani J.

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Modelling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering

Reference20 articles.

1. Horn, B.K., & Schunck, B.G. (1981). Determining optical flow. Artificial intelligence, 17(1-3), 185–203.

2. Russell, D.L., & Young, L.C. (1976). Calculus of variations and control theory: Proceedings of a symposium conducted by the mathematics research center, University of Wisconsin-Madison, September 22-24, 1975. Academic Press, no. 36.

3. Tu, Z., Xie, W., Zhang, D., Poppe, R., Veltkamp, R.C., Li, B., Yuan, J. (2019). A survey of variational and cnn-based optical flow techniques. Signal Processing: Image Communication, 72, 9–24.

4. Zach, C., Pock, T., Bischof, H. (2007). A duality based approach for realtime tv-l1 optical flow. In: DAGM-symposium.

5. Lazcano, V., & Rivera, F. (2019). Gpu based horn-schunck method to estimate optical flow and occlusion. In Gopal, T., & Watada, J. (Eds.) Theory and applications of models of computation (pp. 424–437). Cham: Springer International Publishing.

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