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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
John Leonard Barron, University of Western Ontario, Canada
Marc Daniel, Ecole Superieure d?Ing?enieurs de Luminy, Cedex 9, France
Jean-Luc Mari, Ecole Superieure d?Ing?enieurs de Luminy, Cedex 9, France
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
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