Konferans bildirisi Açık Erişim
Kahraman, Fatih; Kurt, Binnur; Goekmen, Muhittin
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Kurt, Binnur</subfield> <subfield code="u">Istanbul Tech Univ, Dept Comp Engn, TR-34469 Istanbul, Turkey</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Goekmen, Muhittin</subfield> <subfield code="u">Istanbul Tech Univ, Dept Comp Engn, TR-34469 Istanbul, Turkey</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">user-tubitak-destekli-proje-yayinlari</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="a">Creative Commons Attribution</subfield> <subfield code="u">http://www.opendefinition.org/licenses/cc-by</subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="i">isVersionOf</subfield> <subfield code="a">10.81043/aperta.39666</subfield> <subfield code="n">doi</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.81043/aperta.39667</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Robust face alignment for illumination and pose invariant face recognition</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="a">Kahraman, Fatih</subfield> <subfield code="u">Istanbul Tech Univ, Inst Informat, TR-34469 Istanbul, Turkey</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="o">oai:zenodo.org:39667</subfield> <subfield code="p">user-tubitak-destekli-proje-yayinlari</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="2">opendefinition.org</subfield> <subfield code="a">cc-by</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2007-01-01</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="u">https://aperta.ulakbim.gov.trrecord/39667/files/bib-3cd35ae8-44a6-4e12-99e2-6dc803091fde.txt</subfield> <subfield code="z">md5:93f53df9122605ae0dd9958640f21c92</subfield> <subfield code="s">194</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <controlfield tag="005">20210315201825.0</controlfield> <controlfield tag="001">39667</controlfield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">conferencepaper</subfield> </datafield> <datafield tag="711" ind1=" " ind2=" "> <subfield code="a">2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a">In building a face recognition system for real-life scenarios, one usually faces the problem that is the selection of a feature-space and preprocessing methods such as alignment under varying illumination conditions and poses. In this study, we developed a robust face alignment approach based on Active Appearance Model (AAM) by inserting an illumination normalization module into the standard AAM searching procedure and inserting different poses of the same identity into the training set. The modified AAM search can now handle both illumination and pose variations in the same epoch, hence it provides better convergence in both point-to-point and point-to-curve senses. We also investigate how face recognition performance is affected by the selection of feature space as well as the proposed alignment method The experimental results show that the combined pose alignment and illumination normalization methods increase the recognition rates considerably for all feature spaces.</subfield> </datafield> </record>
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