Publication:
A Comparison of Facial Landmark Detection Methods

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dc.contributor.authorsSandikci, Esra Nur; Eroglu Erdem, Cigdem; Ulukaya, Sezer
dc.date.accessioned2022-03-12T16:23:52Z
dc.date.accessioned2026-01-10T19:34:50Z
dc.date.available2022-03-12T16:23:52Z
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.
dc.identifier.doidoiWOS:000511448500210
dc.identifier.isbn978-1-5386-1501-0
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11424/226103
dc.identifier.wosWOS:000511448500210
dc.language.isotur
dc.publisherIEEE
dc.relation.ispartof2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectface analysis
dc.subjectfacial landmarks
dc.subjectFACE ALIGNMENT
dc.titleA Comparison of Facial Landmark Detection Methods
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.title2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)

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