The 3rd Canadian Conference on Computer and Robot Vision (CRV'06) Using 3D Spline Differentiation to Compute Quantitative Optical Flow Quebec City, Quebec, Canada June 07-June 09 ISBN: 0-7695-2542-3
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CRV.2006.84
We show that differentiation via fitting B-splines to the spatio-temporal intensity data comprising an image sequence provides at least the same and usually better 2D Lucas and Kanade optical flow than that computed via Simoncelli?s balanced/matched filters.
Index Terms:
B-Splines, Filters, Differentiation, 2D Optical Flow, Quantitative Error Analysis
Citation:
John Leonard Barron, Marc Daniel, Jean-Luc Mari, "Using 3D Spline Differentiation to Compute Quantitative Optical Flow," crv, pp.11, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06), 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||