An error-weighted regularization algorithm for image motion-field estimation
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Updated: Jul 7, 2026

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
1Dept. of Electr. Eng., Queen's Univ., Kingston, Ont.
Abstract:
Local motion measurement errors are used to guide the global smoothing process in order to preserve motion-field discontinuities. A field-smoothing algorithm based on matching-error weighting is proposed. The added computation is minimal, since it uses byproducts of the local measurement process. The error-weighting functional provides significantly improved motion field estimates, as measured by motion-compensated interpolation performance. However, the mean-square reconstruction error is somewhat higher than that obtained by performing the much more computationally expensive stochastic optimization.
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