<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>sibgrapi.sid.inpe.br 802</site>
		<holdercode>{ibi 8JMKD3MGPEW34M/46T9EHH}</holdercode>
		<identifier>6qtX3pFwXQZeBBx/vStjr</identifier>
		<repository>sid.inpe.br/banon/2002/10.25.09.20</repository>
		<lastupdate>2002:09.23.03.00.00 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/banon/2002/10.25.09.20.33</metadatarepository>
		<metadatalastupdate>2022:06.14.00.11.55 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2002}</metadatalastupdate>
		<doi>10.1109/SIBGRA.2002.1167141</doi>
		<citationkey>GopiKris:2002:FaEfPr</citationkey>
		<title>Fast and efficient projection-based approach for surface reconstruction</title>
		<year>2002</year>
		<numberoffiles>1</numberoffiles>
		<size>5438 KiB</size>
		<author>Gopi, M.,</author>
		<author>Krishnan, Shankar,</author>
		<editor>Gonçalves, Luiz Marcos Garcia,</editor>
		<editor>Musse, Soraia Raupp,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Giraldi, Gilson,</editor>
		<editor>Dreux, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI)</conferencename>
		<conferencelocation>Fortaleza, CE, Brazil</conferencelocation>
		<date>10-10 Oct. 2002</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<abstract>We present a fast and memory efficient algorithm that generates a manifold triangular mesh S passing through a set of unorganized points P {R}^3. Nothing is assumed about the geometry, topology or presence of boundaries in the data set except that P is sampled from a real manifold surface. The speed of our algorithm is derived from a projection-based approach we use to determine the incident faces on a point. Our algorithm has successfully reconstructed the surfaces of unorganized point clouds of sizes varying from 10,000 to 100,000 in about 3--30 seconds on a 250 MHz, R10000 SGI Onyx2. Our technique can be specialized for different kinds of input and applications. For example, our algorithm can be specialized to  handle data from height fields like terrain and range scan, even in the presence of noise. We have successfully generated meshes for range scan data of size 900,000 points in less than 40 seconds.</abstract>
		<language>en</language>
		<targetfile>102.pdf</targetfile>
		<usergroup>administrator</usergroup>
		<visibility>shown</visibility>
		<nexthigherunit>8JMKD3MGPEW34M/46QCSHP</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2022/05.01.04.11 6</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<notes>The conference was held in Fortaleza, CE, Brazil, from October 7 to 10.</notes>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/10.25.09.20</url>
	</metadata>
</metadatalist>