1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/3U3ETBS |
Repository | sid.inpe.br/sibgrapi/2019/09.15.02.10 |
Last Update | 2019:09.15.02.10.34 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2019/09.15.02.10.34 |
Metadata Last Update | 2022:06.14.00.09.42 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2019.00043 |
Citation Key | CardenasCernChav:2019:DySiLa |
Title | Dynamic Sign Language Recognition Based on Convolutional Neural Networks and Texture Maps |
Format | On-line |
Year | 2019 |
Access Date | 2024, May 13 |
Number of Files | 1 |
Size | 2493 KiB |
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2. Context | |
Author | 1 Cardenas, Edwin Jonathan Escobedo 2 Cerna, Lourdes Ramirez 3 Chavez, Guillermo Camara |
Affiliation | 1 Federal University of Ouro Preto 2 National University of Ouro Preto 3 Federal University of Ouro Preto |
Editor | Oliveira, Luciano Rebouças de Sarder, Pinaki Lage, Marcos Sadlo, Filip |
e-Mail Address | edu.escobedo88@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 32 (SIBGRAPI) |
Conference Location | Rio de Janeiro, RJ, Brazil |
Date | 28-31 Oct. 2019 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2019-09-15 02:10:34 :: edu.escobedo88@gmail.com -> administrator :: 2022-06-14 00:09:42 :: administrator -> edu.escobedo88@gmail.com :: 2019 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | CNN sign language texture maps |
Abstract | Sign language recognition (SLR) is a very challenging task due to the complexity of learning or developing descriptors to represent its primary parameters (location, movement, and hand configuration). In this paper, we propose a robust deep learning based method for sign language recognition. Our approach represents multimodal information (RGB-D) through texture maps to describe the hand location and movement. Moreover, we introduce an intuitive method to extract a representative frame that describes the hand shape. Next, we use this information as inputs to two three-stream and two-stream CNN models to learn robust features capable of recognizing a dynamic sign. We conduct our experiments on two sign language datasets, and the comparison with state-of-the-art SLR methods reveal the superiority of our approach which optimally combines texture maps and hand shape for SLR tasks. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Dynamic Sign Language... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Dynamic Sign Language... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://sibgrapi.sid.inpe.br/ibi/8JMKD3MGPEW34M/3U3ETBS |
zipped data URL | http://sibgrapi.sid.inpe.br/zip/8JMKD3MGPEW34M/3U3ETBS |
Language | en |
Target File | PID111.pdf |
User Group | edu.escobedo88@gmail.com |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/3UA4FNL 8JMKD3MGPEW34M/3UA4FPS 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2019/10.25.18.30.33 14 sid.inpe.br/sibgrapi/2022/06.10.21.49 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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 volume |
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7. Description control | |
e-Mail (login) | edu.escobedo88@gmail.com |
update | |
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