Hand Gesture Recognition Based on Segmented Singular Value Decomposition
Identifieur interne : 004A21 ( Istex/Corpus ); précédent : 004A20; suivant : 004A22Hand Gesture Recognition Based on Segmented Singular Value Decomposition
Auteurs : Jing Liu ; Manolya KavakliSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2010.
Abstract
Abstract: The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.
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DOI: 10.1007/978-3-642-15390-7_22
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In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Jing Liu</name><affiliations><json:string>Department of Computing, Macquarie University, Australia</json:string><json:string>E-mail: jliu@ics.mq.edu.au</json:string></affiliations></json:item><json:item><name>Manolya Kavakli</name><affiliations><json:string>Department of Computing, Macquarie University, Australia</json:string><json:string>E-mail: manolya@ics.mq.edu.au</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><abstract>Abstract: The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. 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In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.</p></abstract><textClass><keywords scheme="Book Subject Collection"><list><label>SUCO11645</label><item><term>Computer Science</term></item></list></keywords></textClass><textClass><keywords scheme="Book Subject Group"><list><label>I</label><label>I21017</label><label>I18040</label><label>I13022</label><label>I18032</label><label>I2203X</label><label>I18024</label><item><term>Computer Science</term></item><item><term>Artificial Intelligence (incl. 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Language="En" MediaType="eBook" NumberingDepth="2" NumberingStyle="ContentOnly" OutputMedium="All" TocLevels="0"><BookID>978-3-642-15390-7</BookID><BookTitle>Knowledge-Based and Intelligent Information and Engineering Systems</BookTitle><BookSubTitle>14th International Conference, KES 2010, Cardiff, UK, September 8-10, 2010, Proceedings, Part II</BookSubTitle><BookVolumeNumber>6277</BookVolumeNumber><BookSequenceNumber>6277</BookSequenceNumber><BookDOI>10.1007/978-3-642-15390-7</BookDOI><BookTitleID>212981</BookTitleID><BookPrintISBN>978-3-642-15389-1</BookPrintISBN><BookElectronicISBN>978-3-642-15390-7</BookElectronicISBN><BookChapterCount>67</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2010</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I21017" Priority="1" Type="Secondary">Artificial Intelligence (incl. Robotics)</BookSubject><BookSubject Code="I18040" Priority="2" Type="Secondary">Information Systems Applications (incl.Internet)</BookSubject><BookSubject Code="I13022" Priority="3" Type="Secondary">Computer Communication Networks</BookSubject><BookSubject Code="I18032" Priority="4" Type="Secondary">Information Storage and Retrieval</BookSubject><BookSubject Code="I2203X" Priority="5" Type="Secondary">Pattern Recognition</BookSubject><BookSubject Code="I18024" Priority="6" Type="Secondary">Database Management</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID><SubSeriesID>1244</SubSeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff19"><EditorName DisplayOrder="Western"><GivenName>Rossitza</GivenName><FamilyName>Setchi</FamilyName></EditorName><Contact><Email>Setchi@cf.ac.uk</Email></Contact></Editor><Editor AffiliationIDS="Aff20"><EditorName DisplayOrder="Western"><GivenName>Ivan</GivenName><FamilyName>Jordanov</FamilyName></EditorName><Contact><Email>Ivan.Jordanov@port.ac.uk</Email></Contact></Editor><Editor AffiliationIDS="Aff21"><EditorName DisplayOrder="Western"><GivenName>Robert</GivenName><GivenName>J.</GivenName><FamilyName>Howlett</FamilyName></EditorName><Contact><Email>rjhowlett@kesinternational.org</Email></Contact></Editor><Editor AffiliationIDS="Aff22"><EditorName DisplayOrder="Western"><GivenName>Lakhmi</GivenName><GivenName>C.</GivenName><FamilyName>Jain</FamilyName></EditorName><Contact><Email>Lakhmi.Jain@unisa.edu.au</Email></Contact></Editor><Affiliation ID="Aff19"><OrgDivision>School of Engineering, The Parade</OrgDivision><OrgName>Cardiff University</OrgName><OrgAddress><Postcode>CF24 3AA</Postcode><City>Cardiff</City><Country>UK</Country></OrgAddress></Affiliation><Affiliation ID="Aff20"><OrgDivision>Dept. of Computer Science and Software Engineering, BUckingham Building, Lion Terrace</OrgDivision><OrgName>University of Portsmouth</OrgName><OrgAddress><Postcode>PO1 3HE</Postcode><City>Portsmouth</City><Country>UK</Country></OrgAddress></Affiliation><Affiliation ID="Aff21"><OrgName>KES International</OrgName><OrgAddress><Street>145-157 St. John Street</Street><Postcode>EC1V 4PY</Postcode><City>London</City><Country>UK</Country></OrgAddress></Affiliation><Affiliation ID="Aff22"><OrgDivision>School of Electrical and Information Engineering</OrgDivision><OrgName>University of South Australia</OrgName><OrgAddress><Street>Adelaide, Mawson Lakes Campus</Street><Postcode>5095</Postcode><State>SA</State><Country>Australia</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part3"><PartInfo TocLevels="0"><PartID>3</PartID><PartSequenceNumber>3</PartSequenceNumber><PartTitle>Intelligent Systems</PartTitle><PartChapterCount>22</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Knowledge-Based and Intelligent Information and Engineering Systems</BookTitle></PartContext></PartInfo><Chapter ID="Chap22" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>22</ChapterID><ChapterDOI>10.1007/978-3-642-15390-7_22</ChapterDOI><ChapterSequenceNumber>22</ChapterSequenceNumber><ChapterTitle Language="En">Hand Gesture Recognition Based on Segmented Singular Value Decomposition</ChapterTitle><ChapterFirstPage>214</ChapterFirstPage><ChapterLastPage>223</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2010</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>3</PartID><BookID>978-3-642-15390-7</BookID><BookTitle>Knowledge-Based and Intelligent Information and Engineering Systems</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff23"><AuthorName DisplayOrder="Western"><GivenName>Jing</GivenName><FamilyName>Liu</FamilyName></AuthorName><Contact><Email>jliu@ics.mq.edu.au</Email></Contact></Author><Author AffiliationIDS="Aff23"><AuthorName DisplayOrder="Western"><GivenName>Manolya</GivenName><FamilyName>Kavakli</FamilyName></AuthorName><Contact><Email>manolya@ics.mq.edu.au</Email></Contact></Author><Affiliation ID="Aff23"><OrgDivision>Department of Computing</OrgDivision><OrgName>Macquarie University</OrgName><OrgAddress><Country>Australia</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(<Emphasis Type="Italic">SegSVD</Emphasis>) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Hand Gesture Recognition Based on Segmented Singular Value Decomposition</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Hand Gesture Recognition Based on Segmented Singular Value Decomposition</title></titleInfo><name type="personal"><namePart type="given">Jing</namePart><namePart type="family">Liu</namePart><affiliation>Department of Computing, Macquarie University, Australia</affiliation><affiliation>E-mail: jliu@ics.mq.edu.au</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Manolya</namePart><namePart type="family">Kavakli</namePart><affiliation>Department of Computing, Macquarie University, Australia</affiliation><affiliation>E-mail: manolya@ics.mq.edu.au</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2010</dateIssued><copyrightDate encoding="w3cdtf">2010</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.</abstract><relatedItem type="host"><titleInfo><title>Knowledge-Based and Intelligent Information and Engineering Systems</title><subTitle>14th International Conference, KES 2010, Cardiff, UK, September 8-10, 2010, Proceedings, Part II</subTitle></titleInfo><name type="personal"><namePart type="given">Rossitza</namePart><namePart type="family">Setchi</namePart><affiliation>School of Engineering, The Parade, Cardiff University, CF24 3AA, Cardiff, UK</affiliation><affiliation>E-mail: Setchi@cf.ac.uk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Ivan</namePart><namePart type="family">Jordanov</namePart><affiliation>Dept. of Computer Science and Software Engineering, BUckingham Building, Lion Terrace, University of Portsmouth, PO1 3HE, Portsmouth, UK</affiliation><affiliation>E-mail: Ivan.Jordanov@port.ac.uk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Robert</namePart><namePart type="given">J.</namePart><namePart type="family">Howlett</namePart><affiliation>KES International, 145-157 St. John Street, EC1V 4PY, London, UK</affiliation><affiliation>E-mail: rjhowlett@kesinternational.org</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Lakhmi</namePart><namePart type="given">C.</namePart><namePart type="family">Jain</namePart><affiliation>School of Electrical and Information Engineering, University of South Australia, Adelaide, Mawson Lakes Campus, 5095, SA, Australia</affiliation><affiliation>E-mail: Lakhmi.Jain@unisa.edu.au</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2010</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. 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