Kalmoun EM, Köstler H, Rüde U (2007)
Publication Type: Journal article
Publication year: 2007
Publisher: Elsevier
Book Volume: 25
Pages Range: 1482-1494
Journal Issue: 9
URI: http://www.sciencedirect.com/science/article/pii/S0262885606003696
DOI: 10.1016/j.imavis.2006.12.017
Motivated by recent applications to 3D medical motion estimation, we consider the problem of 3D optical flow computation in real time. The 3D optical flow model is derived from a straightforward extension of the 2D Horn-Schunck model and discretized using standard finite differences. We compare memory costs and convergence rates of four numerical schemes: Gauss-Seidel and multigrid with three different strategies of coarse grid operators discretization: direct coarsening, lumping and Galerkin approaches. Experimental results to compute 3D motion from cardiac C-arm CT images demonstrate that our variational multi-grid based on Galerkin discretization outperforms significantly the Gauss-Seidel method. The parallel implementation of the proposed scheme using domain partitioning shows that the algorithm scales well up to 32 processors on a cluster of AMD Opteron CPUs which consists of four-way nodes connected by an Infiniband network. © 2007.
APA:
Kalmoun, E.M., Köstler, H., & Rüde, U. (2007). 3D optical flow computation using a parallel variational multigrid scheme with application to cardiac C-arm CT motion. Image and Vision Computing, 25(9), 1482-1494. https://doi.org/10.1016/j.imavis.2006.12.017
MLA:
Kalmoun, El Mostafa, Harald Köstler, and Ulrich Rüde. "3D optical flow computation using a parallel variational multigrid scheme with application to cardiac C-arm CT motion." Image and Vision Computing 25.9 (2007): 1482-1494.
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