Publication:
A comparison of facial landmark detection methods [Yüzdeki Karakteristik Noktalari Saptama Yöntemlerinin Kiyaslanmasi]

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dc.contributor.authorsSandikci E.N., Erdem C.E., Ulukaya S.
dc.date.accessioned2022-03-15T02:13:26Z
dc.date.accessioned2026-01-10T18:55:33Z
dc.date.available2022-03-15T02:13:26Z
dc.date.issued2018
dc.description.abstractFace analysis is a rapidly developing research area and facial landmark detection is one of the pre-processing steps. In recent years, many algorithms and comprehensive survey/ challenge papers have been published on facial landmark detection. In this work, we analysed six survey/challenge papers and observed that among open source systems deep learning (TCDCN, DCR) and regression based (CFSS) methods show superior performance. © 2018 IEEE.
dc.identifier.doi10.1109/SIU.2018.8404357
dc.identifier.isbn9781538615010
dc.identifier.urihttps://hdl.handle.net/11424/247914
dc.language.isotur
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFace analysis
dc.subjectFacial landmarks
dc.titleA comparison of facial landmark detection methods [Yüzdeki Karakteristik Noktalari Saptama Yöntemlerinin Kiyaslanmasi]
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage4
oaire.citation.startPage1
oaire.citation.title26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

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