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		<title>Chai et al 2014a - Revision history</title>
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		<updated>2026-05-11T09:40:32Z</updated>
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		<id>http://www.colloquiam.com/wd/index.php?title=Chai_et_al_2014a&amp;diff=195176&amp;oldid=prev</id>
		<title>Scipediacontent: Scipediacontent moved page Draft Content 779724662 to Chai et al 2014a</title>
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				<updated>2021-01-28T22:26:19Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_779724662&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 779724662&quot;&gt;Draft Content 779724662&lt;/a&gt; to &lt;a href=&quot;/public/Chai_et_al_2014a&quot; title=&quot;Chai et al 2014a&quot;&gt;Chai et al 2014a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 22:26, 28 January 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>http://www.colloquiam.com/wd/index.php?title=Chai_et_al_2014a&amp;diff=195175&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  Point clouds are the main output of automatic data collection using laser-scanner technologies. The large numbers of points scanned from pipeline plants make...&quot;</title>
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				<updated>2021-01-28T22:26:15Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  Point clouds are the main output of automatic data collection using laser-scanner technologies. The large numbers of points scanned from pipeline plants make...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Point clouds are the main output of automatic data collection using laser-scanner technologies. The large numbers of points scanned from pipeline plants make the plant reconstruct very difficult. We have developed a system based on the Point cloud Library (PCL), to find, recognize and reconstruct 3D pipes within point-clouds fully automatically. The proposed approach consists of pre-processing point cloud data, segmentation, skeleton extraction and automatic cylinder fitting for pipeline. The presented results shows that the proposed method enables reliable 3D models of pipelines, which could be successfully incorporated into the reconstruction of a plant information modelling method and utilized for, assist maintenance and expansion of existing plants.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://dx.doi.org/10.14257/astl.2014.67.11 http://dx.doi.org/10.14257/astl.2014.67.11]&lt;br /&gt;
&lt;br /&gt;
* [http://pdfs.semanticscholar.org/00b3/d979794bd2aaa12d757c00e0d9194284e2e9.pdf http://pdfs.semanticscholar.org/00b3/d979794bd2aaa12d757c00e0d9194284e2e9.pdf]&lt;br /&gt;
&lt;br /&gt;
* [http://onlinepresent.org/proceedings/vol67_2014/11.pdf http://onlinepresent.org/proceedings/vol67_2014/11.pdf],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2320530889 https://academic.microsoft.com/#/detail/2320530889]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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