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Reference TypeConference Paper (Conference Proceedings)
Last Update2017:
Metadata Last Update2020: administrator
Citation KeyCarmoAlveOliv:2017:FaIdBa
TitleFace identification based on synergism of classifiers in rectified stereo images
DateOct. 17-20, 2017
Access Date2021, Jan. 21
Number of Files1
Size447 KiB
Context area
Author1 Carmo, Diedre
2 Alves, Raul
3 Oliveira, Luciano
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
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeUndergraduate Work
History2017-09-04 17:28:09 :: -> administrator ::
2020-02-20 22:06:46 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Keywordscomputer vision, stereo camera, face identification.
AbstractThis paper proposes a method to identify faces from a stereo camera. Our approach tries to avoid common problems that come with using only one camera that shall arise while detecting from a relatively unstable view in real world applications. The proposed approach exploits the use of a local binary pattern (LBP) to describe the faces in each image of the stereo camera, after detecting the face using the Viola- Jones method. LBP histogram feeds then multilayer perceptron (MLP) and support vector machine classifiers to identify the faces detected in each stereo image, considering a database of target faces. Computational cost problem due to the use of dual cameras are alleviated with the use of co-planar rectified images, achieved through calibration of the stereo camera. Performance is assessed using the well established Yale face dataset, and performance is assessed by using only one or both camera images.
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