Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/4069
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dc.contributor.authorKarahan, M.-
dc.contributor.authorKurt, Hamza-
dc.contributor.authorKasnakoğlu, Coşku-
dc.date.accessioned2021-01-25T11:32:59Z-
dc.date.available2021-01-25T11:32:59Z-
dc.date.issued2020-10
dc.identifier.citationKarahan, M., Kurt, H., and Kasnakoglu, C. (2020, October). Autonomous Face Detection and Tracking Using Quadrotor UAV. In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-4). IEEE.en_US
dc.identifier.isbn978-172819090-7
dc.identifier.urihttps://hdl.handle.net/20.500.11851/4069-
dc.identifier.urihttps://ieeexplore.ieee.org/document/9254469-
dc.description.abstractIn this paper, human face detection and tracking system with a camera of the Quadrotor UAV is proposed. During flight, Quadrotor takes photos of the human face, records videos and sends these photos and videos to the computer with Wi-fi connection. Face detection algorithm detects human face using Viola Jones algorithm. Face detection algorithm can detect multiple faces at the same time. Face tracking algorithm identifies feature points of the face in first frame and track these features in following frames in a video recorded by the Quadrotor UAV's camera. Face detection and face tracking algorithms' performances are evaluated by using photos and videos of the human faces. It could be interpreted that face detection algorithm successfully detect single and multiple faces and face tracking algorithm is competent to track the human face. © 2020 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCamerasen_US
dc.subjectface detectionen_US
dc.subjectface trackingen_US
dc.subjectfeature trackingen_US
dc.subjectoptical flowen_US
dc.subjectQuadrotorrobot vision systemsen_US
dc.subjectUAVen_US
dc.subjectweak classifieren_US
dc.titleAutonomous Face Detection and Tracking Using Quadrotor UAVen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.authorid0000-0002-0749-4205-
dc.authorid0000-0002-9928-727X-
dc.identifier.scopus2-s2.0-85097669222en_US
dc.institutionauthorKurt, Hamza-
dc.institutionauthorKasnakoğlu, Coşku-
dc.identifier.doi10.1109/ISMSIT50672.2020.9254469-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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