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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PF84FS
Repositorysid.inpe.br/sibgrapi/2017/08.17.23.10
Last Update2017:08.17.23.10.13 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.17.23.10.13
Metadata Last Update2022:06.14.00.08.45 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.19
Citation KeyTeodoroBernDigi:2017:SkCoSe
TitleSkin Color Segmentation and Leveshtein Distance Recognition of BSL Signs in Video
FormatOn-line
Year2017
Access Date2024, Oct. 15
Number of Files1
Size2261 KiB
2. Context
Author1 Teodoro, Beatriz Tomazela
2 Bernardes, João
3 Digiampietri, Luciano Antonio
Affiliation1 USP
2 USP
3 USP
EditorTorchelsen, 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 Addressbeatriz.tomazela@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-17 23:10:14 :: beatriz.tomazela@gmail.com -> administrator ::
2022-06-14 00:08:45 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordssign language recognition
image processing
human skin segmentation
Brazilian Sign Language
LIBRAS
AbstractSign language automatic recognition is an important research area with open challenges that aims to mitigate the obstacles in the daily lives of people who are deaf or hard of hearing and increase their integration in the predominantly hearing society in which we live. This paper implements, evaluates and discusses strategies for automatic recognition of Brazilian Sign Language (BSL) signs, which ultimately aims to simplify the communication between deaf signing in BSL and listeners who do not know this sign language, accomplished through the processing of digital videos of people communicating in BSL without the use of colored gloves or data gloves and sensors or the requirement of high quality recordings in laboratories with controlled backgrounds or lighting. An approach divided in several stages was developed and all stages of the proposed system can be considered contributions for future works in sign language recognition or those involving image processing, human skin segmentation, object tracking etc. For the skin color based segmentation stage, in particular, several techniques were implemented and compared and the strategy used for sign recognition, exploring the Leveshtein distance and a voting scheme with a binary classifier, is unusual in this area and showed good results. From the original 600 samples of 30 words, chosen for frequency of use and superposition of sign elements to make recognition more complex, the system was able to correctly segment 422 (70%) signs, for which it reached 100% accuracy in recognition using our strategy. This sign database with 600 samples in video of the chosen 30 word vocabulary is another of this works contributions and is available upon request to the authors.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Skin Color Segmentation...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Skin Color Segmentation...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PF84FS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PF84FS
Languageen
Target FileSkin_Color_Segmentation_and_Leveshtein_Distance.pdf
User Groupbeatriz.tomazela@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 34
sid.inpe.br/sibgrapi/2022/06.10.21.49 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy 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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