<?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>8JMKD3MGPBW34M/3A369CB</identifier>
		<repository>sid.inpe.br/sibgrapi/2011/07.07.18.15</repository>
		<lastupdate>2011:07.07.18.15.06 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/sibgrapi/2011/07.07.18.15.05</metadatarepository>
		<metadatalastupdate>2022:06.14.00.07.09 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2011}</metadatalastupdate>
		<doi>10.1109/SIBGRAPI.2011.24</doi>
		<citationkey>GüntherReinWagnHotz:2011:MeCoPe</citationkey>
		<title>Memory-Efficient Computation of Persistent Homology for 3D Images using Discrete Morse Theory</title>
		<format>DVD, On-line.</format>
		<year>2011</year>
		<numberoffiles>1</numberoffiles>
		<size>3387 KiB</size>
		<author>Günther, David,</author>
		<author>Reininghaus, Jan,</author>
		<author>Wagner, Hubert,</author>
		<author>Hotz, Ingrid,</author>
		<affiliation>Zuse Institute Berlin</affiliation>
		<affiliation>Zuse Institute Berlin</affiliation>
		<affiliation>Institute of Computer Science, Jagiellonian University</affiliation>
		<affiliation>Zuse Institute Berlin</affiliation>
		<editor>Lewiner, Thomas,</editor>
		<editor>Torres, Ricardo,</editor>
		<e-mailaddress>david.guenther@zib.de</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 24 (SIBGRAPI)</conferencename>
		<conferencelocation>Maceió, AL, Brazil</conferencelocation>
		<date>28-31 Aug. 2011</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>persistent homology, Morse-Smale complex, discrete Morse theory, large data.</keywords>
		<abstract>We propose a memory-efficient method that com- putes persistent homology for 3D gray-scale images. The basic idea is to compute the persistence of the induced Morse-Smale complex. Since in practice this complex is much smaller than the input data, significantly less memory is required for the subsequent computations. We propose a novel algorithm that efficiently extracts the Morse-Smale complex based on algorithms from discrete Morse theory. The proposed algorithm is thereby optimal with a computational complexity of O(n2). The per- sistence is then computed using the Morse-Smale complex by applying an existing algorithm with a good practical running time. We demonstrate that our method allows for the computation of persistent homology for large data on commodity hardware.</abstract>
		<language>en</language>
		<targetfile>persistenceLargeData.pdf</targetfile>
		<usergroup>david.guenther@zib.de</usergroup>
		<visibility>shown</visibility>
		<mirrorrepository>sid.inpe.br/banon/2001/03.30.15.38.24</mirrorrepository>
		<nexthigherunit>8JMKD3MGPEW34M/46SKNPE</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2022/05.15.00.56 6</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<agreement>agreement.html .htaccess .htaccess2</agreement>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi/2011/07.07.18.15</url>
	</metadata>
</metadatalist>