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<a href="http://www.ipol.im/pub/art/2013/26/">http://www.ipol.im/pub/art/2013/26/</a><br>
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TV-L1 Optical Flow Estimation<br>
by Javier Sánchez Pérez, Enric Meinhardt-Llopis and Gabriele
Facciolo<br>
Image Processing On Line, vol. 2013, pp. 137–150. <br>
<a class="moz-txt-link-freetext" href="http://dx.doi.org/10.5201/ipol.2013.26">http://dx.doi.org/10.5201/ipol.2013.26</a><br>
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Abstract<br>
This article describes an implementation of the optical flow
estimation method introduced by Zach, Pock and Bischof in 2007. This
method is based on the minimization of a functional containing a
data term using the L1 norm and a regularization term using the
total variation of the flow. The main feature of this formulation is
that it allows discontinuities in the flow field, while being more
robust to noise than the classical approach of Horn and Schunck. The
algorithm is an efficient numerical scheme, which solves a relaxed
version of the problem by alternate minimization.<br>
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