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A Comparative Study on the Performance Analysis of Feature Extractors Used in Augmented Reality Applications under Various Image Conditions   
Yazarlar (2)
Arş. Gör. Ceren AKMAN YAMAN Arş. Gör. Ceren AKMAN YAMAN
Bursa Teknik Üniversitesi, Türkiye
Ergün Gümüş
Bursa Teknik Üniversitesi, Türkiye
Devamını Göster
Özet
Until today, various approaches have been proposed in order to create Augmented Reality (AR) environment where virtual-real integration takes place. One of these approaches is vision-based model, and it is divided into two branches as Marker-Based Augmented Reality (MBAR) and Markerless Augmented Reality (MAR). In the use of MBAR model, a reference image is introduced to the system before, and when this image enters the camera view, an AR environment is created. However, in MAR model, no image is introduced to the system before. Instead, it uses natural  characteristics present in the image, such as edges, corners, and geometrical shapes to create an AR environment. In order to use MAR model, it is necessary to use algorithms which require high processing power and memory capacity. Within the scope of this study, MAR model was chosen as reference and an evaluation on combinations of descriptive extractors (such as ORB, SIFT, and SURF) and matchers (such as Bruteforce, Bruteforce-Hamming, and Flannbase) was presented. In this context, it was aimed that we could obtain knowledge about i) the number of key points and detection time with the use of different descriptor extractors, and ii) the number of matching key points and the amount of positional deviation of a virtual object placed on a real world scene with the use of different matchers. In line with this goal, analyses were made, using different image scales and brightness levels on both PC and mobile platforms. Results showed that, for both platforms, combinations using ORB method could work faster with less deviation than the combinations using other …
Anahtar Kelimeler
Makale Türü Özgün Makale
Makale Alt Türü Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale
Dergi Adı Journal of Innovative Science and Engineering
Dergi ISSN 2602-4217
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili Türkçe
Basım Tarihi 12-2022
Cilt No 6
Sayı 2
Sayfalar 259 / 278
Doi Numarası 10.38088/jise.1061166
Makale Linki http://jise.btu.edu.tr/en/pub/issue/72956/1061166