Interactive Pickup of Three-dimensional Fine Point Cloud Based on GPU
Three-dimensional fine point cloud has gradually become a key data source of three-dimensional model. The large scale point cloud interactive quick pick up is a kind of important operation in the point cloud data processing and applications. Since the point cloud model is composed of massive points,...
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| Veröffentlicht in: | The open electrical and electronic engineering journal 2014-12, Vol.8 (1), p.631-635 |
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| container_title | The open electrical and electronic engineering journal |
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| creator | Huang, Ming Yang, Fang Zhang, Yong Fu, Xinle |
| description | Three-dimensional fine point cloud has gradually become a key data source of three-dimensional model.
The large scale point cloud interactive quick pick up is a kind of important operation in the point cloud data processing
and applications. Since the point cloud model is composed of massive points, the speed of ordinary picking method is
limited. A GPU-based point cloud picking algorithm was thus presented to solve the problem. The basic idea of the algorithm
is that by spatial transformation converting the point cloud to screen space, and then, the point was calculated
which is the nearest to the mouse click point in screen space. The GPU's parallel computing capabilities were used to
achieve spatial transformation and distance comparison by compute shader in this algorithm. So the speed of the
pickup has been increased. The results show that compared with the CPU, the pickup method based on GPU has greater
speed advantage. Especially for the point cloud over 4 million points, the speed of the pickup has been increased 2-3
times faster. |
| doi_str_mv | 10.2174/1874129001408010631 |
| format | Article |
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The large scale point cloud interactive quick pick up is a kind of important operation in the point cloud data processing
and applications. Since the point cloud model is composed of massive points, the speed of ordinary picking method is
limited. A GPU-based point cloud picking algorithm was thus presented to solve the problem. The basic idea of the algorithm
is that by spatial transformation converting the point cloud to screen space, and then, the point was calculated
which is the nearest to the mouse click point in screen space. The GPU's parallel computing capabilities were used to
achieve spatial transformation and distance comparison by compute shader in this algorithm. So the speed of the
pickup has been increased. The results show that compared with the CPU, the pickup method based on GPU has greater
speed advantage. Especially for the point cloud over 4 million points, the speed of the pickup has been increased 2-3
times faster.</description><identifier>ISSN: 1874-1290</identifier><identifier>EISSN: 1874-1290</identifier><identifier>DOI: 10.2174/1874129001408010631</identifier><language>eng</language><ispartof>The open electrical and electronic engineering journal, 2014-12, Vol.8 (1), p.631-635</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Huang, Ming</creatorcontrib><creatorcontrib>Yang, Fang</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>Fu, Xinle</creatorcontrib><title>Interactive Pickup of Three-dimensional Fine Point Cloud Based on GPU</title><title>The open electrical and electronic engineering journal</title><description>Three-dimensional fine point cloud has gradually become a key data source of three-dimensional model.
The large scale point cloud interactive quick pick up is a kind of important operation in the point cloud data processing
and applications. Since the point cloud model is composed of massive points, the speed of ordinary picking method is
limited. A GPU-based point cloud picking algorithm was thus presented to solve the problem. The basic idea of the algorithm
is that by spatial transformation converting the point cloud to screen space, and then, the point was calculated
which is the nearest to the mouse click point in screen space. The GPU's parallel computing capabilities were used to
achieve spatial transformation and distance comparison by compute shader in this algorithm. So the speed of the
pickup has been increased. The results show that compared with the CPU, the pickup method based on GPU has greater
speed advantage. Especially for the point cloud over 4 million points, the speed of the pickup has been increased 2-3
times faster.</description><issn>1874-1290</issn><issn>1874-1290</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNptkMtOwzAURC0EEqXwBWz8A4F7YzuOlxD1JVWii3YdOX4IQ2pXcYrE30MECxasZnQ0msUh5B7hoUTJH7GWHEsFgBxqQKgYXpDZRIsJX_7p1-Qm5zeAqlSKz8hiE0c3aDOGD0d3wbyfTzR5un8dnCtsOLqYQ4q6p8sQvwcpxJE2fTpb-qyzszRFutodbsmV1312d785J4flYt-si-3LatM8bQuDQmGBrpYOpeFKSYmiEkaA6GphjRSy86Iz2nZS2cpp9CCld9aCKJlQomOgOZsT9vNrhpTz4Hx7GsJRD58tQjuZaP8xwb4AUfRPaw</recordid><startdate>20141231</startdate><enddate>20141231</enddate><creator>Huang, Ming</creator><creator>Yang, Fang</creator><creator>Zhang, Yong</creator><creator>Fu, Xinle</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20141231</creationdate><title>Interactive Pickup of Three-dimensional Fine Point Cloud Based on GPU</title><author>Huang, Ming ; Yang, Fang ; Zhang, Yong ; Fu, Xinle</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1591-1e87e17c499771565c505b85dc757bf5bcadb79d6ea1f077fedd0523595b30a43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huang, Ming</creatorcontrib><creatorcontrib>Yang, Fang</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>Fu, Xinle</creatorcontrib><collection>CrossRef</collection><jtitle>The open electrical and electronic engineering journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huang, Ming</au><au>Yang, Fang</au><au>Zhang, Yong</au><au>Fu, Xinle</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Interactive Pickup of Three-dimensional Fine Point Cloud Based on GPU</atitle><jtitle>The open electrical and electronic engineering journal</jtitle><date>2014-12-31</date><risdate>2014</risdate><volume>8</volume><issue>1</issue><spage>631</spage><epage>635</epage><pages>631-635</pages><issn>1874-1290</issn><eissn>1874-1290</eissn><abstract>Three-dimensional fine point cloud has gradually become a key data source of three-dimensional model.
The large scale point cloud interactive quick pick up is a kind of important operation in the point cloud data processing
and applications. Since the point cloud model is composed of massive points, the speed of ordinary picking method is
limited. A GPU-based point cloud picking algorithm was thus presented to solve the problem. The basic idea of the algorithm
is that by spatial transformation converting the point cloud to screen space, and then, the point was calculated
which is the nearest to the mouse click point in screen space. The GPU's parallel computing capabilities were used to
achieve spatial transformation and distance comparison by compute shader in this algorithm. So the speed of the
pickup has been increased. The results show that compared with the CPU, the pickup method based on GPU has greater
speed advantage. Especially for the point cloud over 4 million points, the speed of the pickup has been increased 2-3
times faster.</abstract><doi>10.2174/1874129001408010631</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| title | Interactive Pickup of Three-dimensional Fine Point Cloud Based on GPU |
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