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<!--#include virtual="/header.html" -->
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<p class="inFormHeader">Supplementary Material Page</p>
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<p class="textNormal" style="text-align: center; font-size: 25px;">
<br>
<b>Modeling Temporal Coherence for Optical Flow </b>
</p>
<p class="textNormal" style="text-align: center; font-size: 20px;">
<b><i> ICCV 2011 </i></b>
</p>
<p class="textNormal" style="text-align: center;">
<br><br>
<a href="" style="color: #434952; text-decoration: none;">Sebastian Volz<sup>1</sup></a>
<a href="" style="color: #434952; text-decoration: none;">Andrés Bruhn<sup>1</sup></a>
<a href="" style="color: #434952; text-decoration: none;">Levi Valgaerts<sup>1</sup></a>
<a href="" style="color: #434952; text-decoration: none;">Henning Zimmer<sup>2</sup></a>
<br><br>
<sup>1</sup>Vision and Image Processing Group,<br>
Saarland University, Campus E 1.1, Saarbrücken, Germany<br>
{<a href="" style="color: #434952; text-decoration:none;">bruhn</a>,
<a href="" style="color: #434952; text-decoration:none;">volz</a>}
<!--spambla-->@mmci.uni-saarland.de<br><br>
<sup>2</sup>Mathematical Image Analysis Group,<br>
Saarland University, Campus E1.1, Saarbrücken, Germany<br>
{<a href="" style="color: #434952; text-decoration:none;">valgaerts</a>,
<a href="" style="color: #434952; text-decoration:none;">zimmer</a>}
<!--spambla-->@mia.uni-saarland.de<br><br>
</p>
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<p class="textNormal" style="margin: 0 20px 0 20px; text-align: justify;">
<br>
<b>Abstract</b></br>
<span style="font-style: italic;">
Despite the fact that temporal coherence is undeniably one of the key
aspects when processing video data, this concept has hardly been exploited in recent
optical flow methods.
In this paper, we will present a novel parametrization for multi-frame
optical flow computation that naturally enables us to embed the assumption of a
temporally coherent spatial flow structure, as well as the assumption that the
optical flow is smooth along motion trajectories. While the first assumption is
realized by expanding spatial regularization over multiple frames, the second
assumption is imposed by two novel first- and second-order trajectorial
smoothness terms. With respect to the latter, we investigate an adaptive
decision scheme that makes a local (per pixel) or global (per sequence)
selection of the most appropriate model possible. Experiments show the clear
superiority of our approach when compared to existing strategies for imposing
temporal coherence. Moreover, we demonstrate the state-of-the-art performance
of our method by achieving Top 3 results at the widely used Middlebury benchmark.
</span></br><br><br>
<center><img src="images/set_up.jpg"></center>
<br>
</p>
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<p class="textNormal">
This is a supplementary material page for the paper <b>Modeling Temporal Coherence for
Optical Flow</b>
that has been published at the
<a href="http://www.iccv2011.org/" onclick="window.open('http://www.iccv2011.org/'); return false;">
13th IEEE International Conference on Computer Vision</a> (6-13 Nov. 2011,
Barcelona, Spain).
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<p class="textNormal" style="margin: 0 20px 0 20px; text-align:justify">
<br><b>Downloads</b></br>
<ul class="textNormal" style="margin: 0 0 0 20px;">
<li class="textNormal"><a href="volz_iccv2011_sup.pdf">Supplementary Material</a> [pdf, 14.4MB]</li>
<li class="textNormal"><a href="volz_iccv2011_vid.zip">Supplementary Video</a> [zipped avi, 11MB]</li>
<li class="textNormal"><a href="volz_iccv2011.bib" type="application/octet-stream">Bibtex</a></li>
</ul>
</p>
<p class="textNormal" style="margin: 0 20px 0 20px; text-align:justify">
<br><b>Additional Information</b></br>
<ul class="textNormal" style="margin: 0 0 0 20px;">
<li class="textNormal"><a href="iccv2011_additional_results.shtml">Additional Experimental Results</a></li>
</ul>
</p>
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<br><br>
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