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A new article is available in IPOL:
<a class="moz-txt-link-freetext" href="http://www.ipol.im/pub/art/2013/21/">http://www.ipol.im/pub/art/2013/21/</a><br>
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Robust Optical Flow Estimation<br>
by Javier Sánchez Pérez, Nelson Monzón López, Agustín Salgado de la
Nuez<br>
Image Processing On Line, vol. 2013, pp. 242-260.<br>
<a class="moz-txt-link-freetext" href="http://dx.doi.org/10.5201/ipol.2013.21">http://dx.doi.org/10.5201/ipol.2013.21</a><br>
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Abstract<br>
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In this work, we describe an implementation of the variational
method proposed by Brox et al. in 2004, which yields accurate
optical flows with low running times. It has several benefits with
respect to the method of Horn and Schunck: it is more robust to the
presence of outliers, produces piecewise-smooth flow fields and can
cope with constant brightness changes. This method relies on the
brightness and gradient constancy assumptions, using the information
of the image intensities and the image gradients to find
correspondences. It also generalizes the use of continuous L1
functionals, which help mitigate the effect of outliers and create a
Total Variation (TV) regularization. Additionally, it introduces a
simple temporal regularization scheme that enforces a continuous
temporal coherence of the flow fields.<br>
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