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<channel>
	<title>Project Archive &#8211; Paul Rosen</title>
	<atom:link href="https://cspaul.com/category/projects/project-archive/feed/" rel="self" type="application/rss+xml" />
	<link>https://cspaul.com</link>
	<description>Associate Professor, University of Utah</description>
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		<title>DarkView: Parameter Space Visualization Tool</title>
		<link>https://cspaul.com/darkview-parameter-space-visualization-tool/</link>
		
		<dc:creator><![CDATA[paul.rosen]]></dc:creator>
		<pubDate>Thu, 11 Apr 2013 18:50:27 +0000</pubDate>
				<category><![CDATA[Project Archive]]></category>
		<guid isPermaLink="false">http://www.cspaul.com/wordpress/?p=194</guid>

					<description><![CDATA[DarkView: Parameter Space Visualization Tool DarkView is a parameter space visualization tool under development in collaboration with Pearl Sandick for]]></description>
										<content:encoded><![CDATA[<div style="height: 275px;">
<div style="float: right; background-color: white; padding: 0px 10px 10px 25px;"><img decoding="async" style="box-shadow: 5px 5px 5px #888888; border-style: solid; border-width: 1px;" src="/software/darkview/darkview-screenshot-thumb-130210.jpg" alt="screenshot" width="350" /></div>
<h3 style="display: inline;">DarkView: Parameter Space Visualization Tool</h3>
<p><a href="/darkview-parameter-space-visualization-tool/">DarkView</a> is a parameter space visualization tool under development in collaboration with <a href="http://www.physics.utah.edu/~sandick/">Pearl Sandick</a> for the purpose of parameter space exploration in particle physics.</p>
<p><!--


<div style="float: right; padding: 60px 10px 10px 25px;">

<a href="/darkview-parameter-space-visualization-tool/">Continue to Project</a>

</div>


--></p>
</div>
<p><span id="more-194"></span></p>
<div style="float: right; background-color: white; padding: 25px 10px 25px 25px;">
<p><img decoding="async" style="box-shadow: 5px 5px 5px #888888; border-style: solid; border-width: 1px;" src="/software/darkview/darkview-screenshot-thumb-130210.jpg" alt="screenshot" height="200" /></p>
</div>
<p>&nbsp;</p>
<h3 style="display: inline;">About</h3>
<p>DarkView is a parameter space visualization tool under development in collaboration with <a href="http://www.physics.utah.edu/~sandick/">Pearl Sandick</a> for the purpose of parameter space exploration in particle physics.</p>
<h3 style="display: inline;">Software</h3>
<p>Version 0.13</p>
<ul>
<li><a href="/software/darkview/darkview-source_code-130411.zip">Source Code (567 KB)</a></li>
<li><a href="/software/darkview/darkview-setup_x64-130411.exe">Windows 64-bit (4.6 MB)</a></li>
<li><a href="/software/darkview/darkview-setup-130411.dmg">Mac OS X (8.5 MB)</a></li>
</ul>
<p>Version 0.11</p>
<ul>
<li><a href="/software/darkview/darkview-source_code-130210.zip">Source Code (725 KB)</a></li>
<li><a href="/software/darkview/darkview-setup_x64-130210.exe">Windows 64-bit (4.6 MB)</a></li>
<li><a href="/software/darkview/darkview-setup-130210.dmg">Mac OS X (7.8 MB)</a></li>
</ul>
<p>Version 0.1</p>
<ul>
<li><a href="/software/darkview/darkview-source_code-130105.zip">Source Code (455 KB)</a></li>
<li><a href="/software/darkview/darkview-setup_win32-130105.exe">Windows 32-bit (4.0 MB)</a></li>
<li><a href="/software/darkview/darkview-setup_x64-130105.exe">Windows 64-bit (4.6 MB)</a></li>
<li><a href="/software/darkview/darkview-setup-130105.dmg">Mac OS X (7.8 MB)</a></li>
</ul>
<p>Building may also require:</p>
<ul>
<li><a href="http://qt-project.org/">Qt 4.8</a></li>
</ul>
<h3 style="display: inline;">Sample Data</h3>
<ul>
<li>Sample Data 1: <a href="/software/darkview/darkview-sample1_input-130210.zip">Input (1.1 MB)</a> | <a href="/software/darkview/darkview-sample1_output-130210.zip">Output (850 KB)</a></li>
<li>Sample Data 2: <a href="/software/darkview/darkview-sample2_input-130210.zip">Input (130 KB)</a> | <a href="/software/darkview/darkview-sample2_output-130210.zip">Output (25 KB)</a></li>
<li>Sample Data 3: <a href="/software/darkview/darkview-sample3_input-130210.zip">Input (82 KB)</a> | <a href="/software/darkview/darkview-sample3_output-130210.zip">Output (380 KB)</a></li>
<li style="display: inline;"></li>
<li style="display: inline;"></li>
</ul>
<h3 style="display: inline;">Release History</h3>
<p>4/11/2013: Version 0.13</p>
<ul>
<li>Minor bug fixes</li>
<li>Mac OSX performance problems corrected</li>
</ul>
<p>3/26/2013: Version 0.12</p>
<ul>
<li>Minor bug fixes</li>
<li>Help and about context menus added</li>
<li>Scale added to scatterplot view</li>
</ul>
<p>2/10/2013: Version 0.11</p>
<ul>
<li>Minor bug fixes</li>
<li>Pearson Correlation now used for coloring</li>
<li>Progressive rendering for more responsive visualization</li>
<li>Parser for labels allows new tags to produce greek characters (\sigma, \nu, and \gamma)</li>
</ul>
<p>1/5/2013: Version 0.1 (Initial Release)</p>
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			</item>
		<item>
		<title>Rectilinear Texture Warping for Fast Adaptive Shadow Mapping</title>
		<link>https://cspaul.com/projects-rtw/</link>
		
		<dc:creator><![CDATA[paul.rosen]]></dc:creator>
		<pubDate>Fri, 22 Mar 2013 18:48:41 +0000</pubDate>
				<category><![CDATA[Project Archive]]></category>
		<guid isPermaLink="false">http://www.cspaul.com/wordpress/?p=190</guid>

					<description><![CDATA[RTW is an efficient method for adaptively sampling a shadow map using a set of user/developer-defined heuristics. RTW is both memory and computationally efficient, delivering exceedingly high-quality results in real-time.]]></description>
										<content:encoded><![CDATA[

<table>
 <tbody>
  <tr style="border-width: 0px;">
   <td style="border-width: 0px;" width="240">
    <img decoding="async" width="225" src="https://cspaul.com/wordpress/wp-content/uploads/2022/11/Rosen.2011.jpg" />
   </td>
   <td style="border-width: 0px;">
    <p style="margin:0;"><strong>
     <span><a href="#">Rectilinear Texture Warping For Fast Adaptive Shadow Mapping</a></span></strong><br />
     <span><b>Paul Rosen</b> </span><br />
     <span><em>Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games</em>, 2012</span></p>
   </td>
  </tr>
 </tbody>
</table>

<h3>Abstract</h3>
<div><p>Conventional shadow mapping relies on uniform sampling for producing
hard shadow in an efficient manner. This approach trades image quality
in favor of efficiency. A number of approaches improve upon shadow
mapping by combining multiple shadow maps or using complex data structures
to produce shadow maps with multiple resolutions. By sacrificing
some performance, these adaptive methods produce shadows that closely
match ground truth.

This paper introduces Rectilinear Texture Warping (RTW) for efficiently
generating adaptive shadow maps. RTW images combine the advantages
of conventional shadow mapping &#8211; a single shadow map, quick construction,
and constant time pixel shadow tests, with the primary advantage
of adaptive techniques &#8211; shadow map resolutions which more closely
match those requested by output images. RTW images consist of a conventional
texture paired with two 1-D warping maps that form a rectilinear
grid defining the variation in sampling rate. The quality of shadows
produced with RTW shadow maps of standard resolutions, i.e. 2,048&#215;2,048
texture for 1080p output images, approaches that of raytraced results
while low overhead permits rendering at hundreds of frames per second.</p></div>

<h3>Video</h3>
<div><p><center>
<iframe width="640" height="360" src="https://www.youtube.com/embed/Pc2jhlyOh_U" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</center></p></div>

<h3>Downloads</h3>
<div><p>
<a href="http://www.cspaul.com/publications/Rosen.2012.I3D.pdf" class="media" title="http://www.cspaul.com/publications/Rosen.2012.I3D.pdf" rel="nofollow"><img decoding="async" src="https://cspaul.com/wordpress/wp-content/uploads/2022/11/new_acrobat_icon.png" style="height: 60px;" class="media" title="Download the Paper" alt="Download the Paper" /></a>
<a href="http://www.cspaul.com/publications/rosen2012rectilinear.bib" class="media" title="http://www.cspaul.com/publications/rosen2012rectilinear.bib"  rel="nofollow"><img decoding="async" src="https://cspaul.com/wordpress/wp-content/uploads/2022/11/new_bib_icon.png" style="height: 60px;" class="media" title="Download the BiBTeX" alt="Download the BiBTeX" /></a>
</p></div>

<h3>Citation</h3>
<div><p>
<b>Paul Rosen</b>.  Rectilinear Texture Warping For Fast Adaptive Shadow Mapping.  <em>Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games</em>, 2012.
</p>
</div>
<h3>Bibtex</h3>
<div>
<pre class="code">

@inproceedings{rosen2012rectilinear,
  title = {Rectilinear Texture Warping For Fast Adaptive Shadow Mapping},
  author = {Rosen, Paul},
  booktitle = {Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and
    Games},
  series = {I3D},
  pages = {151--158},
  year = {2012},
  keywords = {adaptive sampling, rendering, shadow algorithms},
  abstract = {Conventional shadow mapping relies on uniform sampling for producing hard
    shadow in an efficient manner. This approach trades image quality in favor of
    efficiency. A number of approaches improve upon shadow mapping by combining multiple
    shadow maps or using complex data structures to produce shadow maps with multiple
    resolutions. By sacrificing some performance, these adaptive methods produce shadows
    that closely match ground truth. This paper introduces Rectilinear Texture Warping (RTW)
    for efficiently generating adaptive shadow maps. RTW images combine the advantages of
    conventional shadow mapping - a single shadow map, quick construction, and constant time
    pixel shadow tests, with the primary advantage of adaptive techniques - shadow map
    resolutions which more closely match those requested by output images. RTW images
    consist of a conventional texture paired with two 1-D warping maps that form a
    rectilinear grid defining the variation in sampling rate. The quality of shadows
    produced with RTW shadow maps of standard resolutions, i.e. 2,048x2,048 texture for
    1080p output images, approaches that of raytraced results while low overhead permits
    rendering at hundreds of frames per second.}
}

</pre>
</div>
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			</item>
		<item>
		<title>TC: Node Trajectory Compressor</title>
		<link>https://cspaul.com/tc-node-trajectory-compressor/</link>
		
		<dc:creator><![CDATA[paul.rosen]]></dc:creator>
		<pubDate>Wed, 16 Jan 2013 18:49:43 +0000</pubDate>
				<category><![CDATA[Project Archive]]></category>
		<guid isPermaLink="false">http://www.cspaul.com/wordpress/?p=192</guid>

					<description><![CDATA[TC: Node Trajectory Compressor TC is a set of compression algorithms designed for lossy compression of time varying node positional]]></description>
										<content:encoded><![CDATA[<div style="height:275px;">
<div style="float: right; background-color: white; padding: 10px 10px 10px 25px;">
        <img decoding="async" alt="screenshot" width="350" style="box-shadow: 5px 5px 5px #888888; border-style: solid; border-width: 1px;" src="http://www.cspaul.com/software/tc/tc-screenshot-thumb-130110.jpg" />
    </div>
<h3 style="display: inline;">TC: Node Trajectory Compressor</h3>
<p>
        <a href="http://www.cspaul.com/wordpress/tc-node-trajectory-compressor/">TC</a> is a set of compression algorithms designed for lossy compression of time varying node positional data. The original algorithms were designed in collaboration with <a href="http://www.cs.purdue.edu/~popescu">Voicu Popescu</a> though he is not involved in the current software development. Details of the algorithms used are presented in the [[publications:Rosen.2011.TVCG|paper]] reporting our results.
    </p>
<p> <!--   

<div style="float: right; padding: 20px 10px 10px 25px;">
    

<p><a href="http://www.cspaul.com/wordpress/tc-node-trajectory-compressor/">Continue to Project</a></p>


    </div>

 -->
</div>
<p><span id="more-192"></span></p>
<div style="float: right; background-color: white; padding: 25px 10px 25px 25px;">
<p><img decoding="async" alt="screenshot" height="200" style="box-shadow: 5px 5px 5px #888888; border-style: solid; border-width: 1px;" src="http://www.cspaul.com/software/tc/tc-screenshot-thumb-130110.jpg" /></p>
</div>
<h3 style="display: inline;">About</h3>
<p>TC is a set of compression algorithms designed for lossy compression of time varying node positional data. The original algorithms were designed in collaboration with <a href="http://www.cs.purdue.edu/~popescu">Voicu Popescu</a> though he is not involved in the current software development. Details of the algorithms used are presented in the <a href="http://www.cspaul.com/wordpress/publications_rosen-2011-tvcg/">paper</a> reporting our results.</p>
<h3 style="display: inline;">Software</h3>
<ul>
<li><a href="http://www.cspaul.com/software/tc/tc-source_code-130116.zip">Source Code and Sample Data (122 KB)</a></li>
</ul>
<p>Building may also require:</p>
<ul>
<li><a href="http://qt-project.org">Qt 4.8</a></li>
<li><a href="http://tclap.sourceforge.net/">TCLAP</a></li>
</ul>
<h3 style="display: inline;">Release History</h3>
<ul>
<li>1/16/2013: Version 0.11 Released</li>
<li>1/10/2013: Version 0.1 (Initial) Release</li>
</ul>
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