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<h1 class="title is-1 publication-title">Photogrammetric Reconstruction of a Stolen Statue</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a>Z. Liu</a><sup>1,2</sup>,</span>
<span class="author-block">
<a>E.L. Doubrovski</a><sup>1</sup>,</span>
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<a>J.M.P. Geraedts</a><sup>1</sup>,
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<a>W. Wang</a><sup>3,2</sup>,
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<span class="author-block">
<a>Y. Yam</a><sup>2</sup>,
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<a>C.C.L. Wang</a><sup>4</sup>,
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<span class="author-block"><sup>1</sup>Delft University of Technology,</span>
<span class="author-block"><sup>2</sup>Centre for Perceptual and Interactive Intelligence (CPII),</span>
<span class="author-block"><sup>3</sup>The Chinese University of Hong Kong,</span>
<span class="author-block"><sup>4</sup>The University of Manchester</span>
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<p>
In this paper, we propose a method to reconstruct a digital 3D model of a stolen/damaged
statue using photogrammetric methods. This task is challenging because the number of available
photos for a stolen statue is in general very limited -- especially the side/back view photos.
Besides using standard structure-from-motion and multi-view stereo methods, we match image pairs
with low overlap using sliding windows and maximize the normalized cross-correlation (NCC) based
patch-consistency so that the image pairs can be well aligned into a complete model to build the
3D mesh surface. Our method is based on the prior of the planar side on the statue's pedestal,
which can cover a large range of statues. We hope this work will motivate more research efforts
for the reconstruction of those stolen/damaged statues and heritage preservation.
</p>
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<pre><code>@article{liu2023statue,
author = {Liu, Zishun and Doubrovski, Eugeni L. and Geraedts, Jo M. P. and Wang, Wenting and Yam, Yeung and Wang, Charlie C. L.},
title = {Photogrammetric Reconstruction of a Stolen Statue},
journal = {Eurographics Short Papers},
year = {2023},
}</code></pre>
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<h2 class="title">Acknowledgements</h2>
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This project is supported by the Centre for Perceptual and Interactive Intelligence (CPII) Limited in Hong Kong.
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This project is supported by the Centre for Perceptual and Interactive Intelligence (CPII) Limited in Hong Kong.
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<p>
This website is borrowed from the <a href="https://github.com/nerfies/nerfies.github.io">Nerfies</a>.
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