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DAGM
2007
Springer

Selection of Local Optical Flow Models by Means of Residual Analysis

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Selection of Local Optical Flow Models by Means of Residual Analysis
Abstract. This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric models of local optical flow. These models give rise to parameter estimation problems with highly correlated errors in variables (EIV). Regression is hence performed by equilibrated total least squares. The authors suggest to adaptively select motion models by testing local empirical regression residuals to be in accordance with the probability distribution that is theoretically predicted by the EIV model. Motion estimation with residual-based model selection is examined on artificial sequences designed to test specifically for the properties of the model selection process. These simulations indicate a good performance in the exclusion of inappropriate models and yield promising results in model complexity control.
Björn Andres, Fred A. Hamprecht, Christoph S.
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where DAGM
Authors Björn Andres, Fred A. Hamprecht, Christoph S. Garbe
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