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dc.contributor.authorTosun, Umut
dc.date.accessioned2021-02-19T21:29:44Z
dc.date.available2021-02-19T21:29:44Z
dc.date.issued2019
dc.identifier.issn2587-2680
dc.identifier.issn2587-246X
dc.identifier.urihttps://doi.org/10.17776/csj.638297
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TXpJeE1UVTNOdz09
dc.identifier.urihttps://hdl.handle.net/20.500.12868/1157
dc.description.abstractThe algorithms that extract keypoints and descriptors in augmented reality applications are getting more and more important in terms of performance. Criterions like time and correct matching of points gain more impact according to the type of application. In this paper, the performance of the algorithms used to identify an image using keypoint and descriptor extraction is studied. In the context of this research, main criterion like the number of keypoints and descriptors that the algorithms extract, algorithm execution time, and the quality of keypoints and descriptors extracted are considered as the performance metrics. Same data stacks were used for obtaining comparison results. In addition to comparisons for a group of well-known augmented reality applications, the best performing algorithms for varying applications were also suggested. C++ language and OpenCV library were used for the implementation of the augmented reality algorithms compared.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBiyoloji Çeşitliliğinin Korunmasıen_US
dc.subjectBiyolojien_US
dc.subjectKimya, Analitiken_US
dc.subjectKimya, Uygulamalıen_US
dc.subjectKimya, Tıbbien_US
dc.subjectKimya, Organiken_US
dc.subjectFizikokimyaen_US
dc.subjectFizik, Atomik ve Moleküler Kimyaen_US
dc.subjectFizik, Katı Halen_US
dc.subjectFizik, Akışkanlar ve Plazmaen_US
dc.subjectFizik, Matematiken_US
dc.subjectFizik, Nükleeren_US
dc.subjectFizik, Partiküller ve Alanlaren_US
dc.subjectBilgisayar Bilimleri, Bilgi Sistemlerien_US
dc.subjectMühendislik, Kimyaen_US
dc.subjectİnşaat Mühendisliğien_US
dc.subjectÇevre Mühendisliğien_US
dc.subjectMühendislik, Jeolojien_US
dc.subjectMühendislik, Makineen_US
dc.subjectGıda Bilimi ve Teknolojisien_US
dc.titleComparative analysis of the feature extraction performance of augmented reality algorithmsen_US
dc.typearticleen_US
dc.contributor.departmentALKÜen_US
dc.contributor.institutionauthorTosun, Umut
dc.identifier.doi10.17776/csj.638297
dc.identifier.volume40en_US
dc.identifier.issue4en_US
dc.identifier.startpage958en_US
dc.identifier.endpage966en_US
dc.relation.journalCumhuriyet Science Journalen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanen_US


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