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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M9HLNS
Repositorysid.inpe.br/sibgrapi/2016/08.16.02.19
Last Update2016:08.16.02.22.05 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/08.16.02.19.34
Metadata Last Update2022:05.18.22.21.07 (UTC) administrator
Citation KeySantosFernBeze:2016:GeReSy
TitleHAGR-D: A Gesture Recognition System based on CIPBR Algorithm
FormatOn-line
Year2016
Access Date2024, May 03
Number of Files1
Size592 KiB
2. Context
Author1 Santos, Diego George da Silva
2 Fernandes, Bruno José Torres
3 Bezerra, Byron Leite Dantas
Affiliation1 Universidade de Pernambuco
2 Universidade de Pernambuco
3 Universidade de Pernambuco
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressdiego.thuran@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2016-08-16 02:22:05 :: diego.thuran@gmail.com -> administrator :: 2016
2022-05-18 22:21:07 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsCIPBR
HMM
DTW
Gesture Recognition
AbstractGesture recognition has been an area of great interest and study in recent years due to the evolution of technology and computers processing power, generating a higher degree in the Interaction Human Computer (IHC). These advances now allow communication between man and machine through hand gestures or entire body, especially in games, after the advent of Microsoft Kinect and other depth sensors. This paper proposes a dynamic gesture recognition system for user hand. The system is evaluated in two bases of dynamic hand gestures from the literature. The experiments show that the proposed model overcomes other algorithms presented in the literature in hand gesture recognition tasks, achieving a classification rate of 97.49\% in the MSRGesture3D dataset and 98.43\% in the RPPDI dynamic gesture dataset.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > HAGR-D: A Gesture...
doc Directory Contentaccess
source Directory Content
sibgrap.pdf 15/08/2016 23:19 599.3 KiB 
agreement Directory Content
agreement.html 15/08/2016 23:19 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M9HLNS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M9HLNS
Languageen
Target Filesibgrap.pdf
User Groupdiego.thuran@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 7
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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