Identity statement area | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 8JMKD3MGPAW/3PHJJAP |
Repository | sid.inpe.br/sibgrapi/2017/09.01.15.53 |
Last Update | 2017:09.01.15.53.38 lucasthund3r@gmail.com |
Metadata | sid.inpe.br/sibgrapi/2017/09.01.15.53.38 |
Metadata Last Update | 2020:02.20.22.06.46 administrator |
Citation Key | AmaralLimaVieiViei:2017:ReGeEs |
Title | Reconhecimento de gestos estáticos da mão usando a Transformada de Distância e aplicações em Libras  |
Format | On-line |
Year | 2017 |
Date | Oct. 17-20, 2017 |
Access Date | 2021, Jan. 21 |
Number of Files | 1 |
Size | 958 KiB |
Context area | |
Author | 1 Amaral, Lucas 2 Lima, Givanildo 3 Vieira, Tiago 4 Vieira, Thales |
Affiliation | 1 Universidade Federal de Alagoas 2 Universidade Federal de Alagoas 3 Universidade Federal de Alagoas 4 Universidade Federal de Alagoas |
Editor | Torchelsen, Rafael Piccin Nascimento, Erickson Rangel do Panozzo, Daniele Liu, Zicheng Farias, Mylène Viera, Thales Sacht, Leonardo Ferreira, Nivan Comba, João Luiz Dihl Hirata, Nina Schiavon Porto, Marcelo Vital, Creto Pagot, Christian Azambuja Petronetto, Fabiano Clua, Esteban Cardeal, Flávio |
e-Mail Address | lucasthund3r@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 30 (SIBGRAPI) |
Conference Location | Niterói, RJ |
Book Title | Proceedings |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Tertiary Type | Undergraduate Work |
History | 2017-09-01 15:53:38 :: lucasthund3r@gmail.com -> administrator :: 2020-02-20 22:06:46 :: administrator -> :: 2017 |
Content and structure area | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Transformada de Distância, Redes Neurais Convolucionais, Gestos de Libras. |
Abstract | In this paper we propose a method to recognize static hand gestures from depth images. We first segment the hand from the background, and then compute the Distance Transform to train a Convolutional Neural Network (CNN) that is later used to classify hand poses. In order to evaluate our method in a practical context, we collected a dataset containing 1400 images representing 14 different hand configurations representing signs of the Brazilian Sign Language (Libras). Our method achieved an average recognition rate of 96.42. |
source Directory Content | there are no files |
agreement Directory Content | |
Conditions of access and use area | |
data URL | http://urlib.net/rep/8JMKD3MGPAW/3PHJJAP |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PHJJAP |
Language | pt |
Target File | Artigo_Distancia.pdf |
User Group | lucasthund3r@gmail.com |
Visibility | shown |
Update Permission | not transferred |
Allied materials area | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3PJT9LS 8JMKD3MGPAW/3PKCC58 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
Notes area | |
Empty Fields | accessionnumber archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
| |