Computing inverse optical flow

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where ∇It+1 is the image gradient at W(x; u). ∂W ∂u denotes the Jacobian of the warp. Writing the partial derivatives in ∂W ∂u with respect to a column vector as row vectors, this simply becomes the 2 × 2 identity matrix for the case of optical flow. There is a closed-form solution for parameter update ∆u using a least-squares formulation. Setting to zero the partial derivative of eq. (3) with ...

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ژورنال

عنوان ژورنال: Pattern Recognition Letters

سال: 2015

ISSN: 0167-8655

DOI: 10.1016/j.patrec.2014.09.009