Uçan nesnelerin otomatik tespit ve takibi için yeni bir yaklaşım

Bu çalışmada yerden havayatakip görevlerinde kullanılan video sistemlerinin uçan nesneleri otomatikolarak tespit ve takip etmesi için yeni bir metot sunulmaktadır. Bu yaklaşımdauçan bir nesnenin varlığının tespiti için Standart Sapma bilgisinin kullanıldığıbir metot geliştirilmiştir. Tespit sonrası takip için ölçüm verisi takibe uygunhale getirilir, bu amaçla uçan nesnenin arka fona göre daha baskın hale gelmesisağlanır. Hedefin takibi için gerçek zamanlı performans verebilen genlikbilgisi ilave edilmiş Etkileşimli Çoklu Model Olasılıksal Veri İlişkilendirme(EÇMOVİ-GB) algoritması kullanılmıştır.  EÇMOVİ-GB algoritması temelde nokta verisi takibinde kullanılan bir algoritmaolmakla birlikte bu çalışmada video takibinde kullanılabilirliği gösterilmiştir.Bu amaçla örneklenen video çerçevelerinin genlik bilgileri uygun olarakkodlanarak nokta verisi haline getirilir ve takip bu veri üzerindengerçekleştirilir. Böylece hedefin otomatik olarak tespit edildiği, takibinbaşlatıldığı ve sürdürüldüğü bir algoritma geliştirilmiştir. Algoritma değişikmanevra, hedef tipleri ve arka fon gürültü durumları için incelenerek, başarılısonuçlar elde edilmiştir.

A novel approach for automatic detection and tracking of flying objects

Inthis study, a new method is presented to automatically detect and track flyingobjects through video systems that are used for surface to air tracking tasks. Inthis approach, a method has been developed in which Standard Deviation is usedto determine the presence of a flying object. The measurement data is adaptedto track, so that the flying object becomes more dominant than the background.In order to track the detected target in real time, Interacting Multiple ModelProbabilistic Data Association with Amplitude Information (IMMPDA-AI) algorithm is used. Although the IMMPDA-AI algorithm is mainly apoint tracking algorithm, in this study, its applicability to video tracking isshown. For this purpose, the amplitude information of the sampled video framesis encoded as point data and the tracking is performed on this data. Thus, analgorithm has been developed in which the target is automatically detected,track initiated and continued. The algorithm is evaluated for differentmaneuvers, target types and clutter situations, and successful results areobtained.

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