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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JT78H2
Repositorysid.inpe.br/sibgrapi/2015/07.23.04.57
Last Update2015:07.23.04.57.25 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2015/07.23.04.57.25
Metadata Last Update2022:05.18.22.21.00 (UTC) administrator
Citation KeyRameshGopaChat:2015:EySeCh
TitleEyebrow segmentation and characterization using energy estimation and K-Means clustering
FormatOn-line
Year2015
Access Date2024, May 06
Number of Files1
Size945 KiB
2. Context
Author1 Ramesh, Aditya
2 Gopalakrishnan, Anand
3 Chaturvedi, Ashvini
Affiliation1 National Institute of Technology Karnataka, Surathkal, India
2 National Institute of Technology Karnataka, Surathkal, India
3 National Institute of Technology Karnataka, Surathkal, India
EditorVieira, Thales Miranda de Almeida
Mello, Vinicius Moreira
e-Mail Addressaditya_2806@hotmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2015-07-23 04:57:25 :: aditya_2806@hotmail.com -> administrator ::
2022-05-18 22:21:00 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordseyebrow parameters
segmentation
K-means
biometric
facial expression
AbstractThe eyebrow is an important feature point in a facial image. The data from a segmented eyebrow can be used as a cue for gender determination, mood analysis, facial expression recognition, non-verbal communication and biometric purposes. In this paper, we present a novel method to segment the eyebrow and characterize the state of the eyebrow based on the evaluation of a few key parameters such as thickness and archness of the eyebrow and distance of the eyebrow from the eye. Our technique involves obtaining a box containing the eye and eye brow region using Viola-Jones algorithm. We then segment out the skin region in this box by using the fact that the skin is abundant in its red component as compared to the eye and eyebrows. Further, we perform energy based thresholding to detect the darker regions in this box and then perform K-means clustering to obtain the best possible segmentation for the eyebrow.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2015 > Eyebrow segmentation and...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JT78H2
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JT78H2
Languageen
Target FileSibgrapi_AR_cam_ready.pdf
User Groupaditya_2806@hotmail.com
administrator
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 9
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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