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dc.contributor.authorAcar, Canen_US
dc.contributor.authorAtlas, Ardaen_US
dc.contributor.authorÇevik, Korayen_US
dc.contributor.authorÖlmez İsaen_US
dc.contributor.authorÜnlü, Mustafaen_US
dc.contributor.authorÖzkan, Deryaen_US
dc.contributor.authorDuygulu, Pınaren_US
dc.coverage.spatialEskisehir, Turkeyen_US
dc.date.accessioned2016-02-08T11:43:24Z
dc.date.available2016-02-08T11:43:24Z
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/11693/27067
dc.descriptionDate of Conference: 11-13 June 2007en_US
dc.description.abstractPeople are the most important subjects in news videos and for proper retrieval of people images; face detection is a very crucial step. However, face detection and recognition in news videos is a very challenging task due to the huge irregularities and high noise level in the data. In addition to that, with different face detection algorithms, the number and the type of the faces may differ. In this study, in order to get the best performance from existing methods, systematic evaluation of these methods is performed. In the experiments, news videos from TRECVID 2006 data set are used and for evaluation four different face detection methods are chosen.en_US
dc.language.isoTurkishen_US
dc.source.title2007 IEEE 15th Signal Processing and Communications Applicationsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2007.4298778en_US
dc.subjectChallenging tasken_US
dc.subjectData setsen_US
dc.subjectFace Detectionen_US
dc.subjectFace detection algorithmsen_US
dc.subjectFace detection and recognitionen_US
dc.subjectFace detection methodsen_US
dc.subjectNews videosen_US
dc.subjectNoise levelsen_US
dc.subjectSystematic evaluationen_US
dc.subjectTRECVIDen_US
dc.subjectAlgorithmsen_US
dc.subjectSignal detectionen_US
dc.subjectSignal processingen_US
dc.subjectFace recognitionen_US
dc.titleSystematic evaluation of face detection algorithms on news videosen_US
dc.title.alternativeYüz bulma yöntemlerinin haber videolari için sistematik karşilaştirilmasien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.identifier.doi10.1109/SIU.2007.4298778en_US
dc.publisherIEEEen_US


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