Kalman Filtresine Dayalı Görsel Hedef Tespiti ve Takibi

Bu çalışmada, otonom uçaklarda çarpışmayı ve hedef takibini önlemek amacıyla, Kalman filtresine dayalı hedef tespit ve takip problemlerine uygun çözümler sunulmuştur. Kalman Filtre uygulaması için birden fazla nesnenin takibini kolaylaştıran hareket tabanlı izleme yöntemi kullanılmıştır. Hareketli nesnelerin algılanması için bir arka plan çıkarma algoritması kullanılırken, gürültüyü ortadan kaldırmak için ön plan maskesine düzeltici eylemler uygulanmış ve hareketli nesnelere karşılık gelen bağlı piksel grupları belirlenmiştir. Kullanılan görüntü, havada asılı duran bir drone tarafından çekilen bir görüntüyü temsil etmektedir. Takip edilen birden fazla hedef, engelin arkasında kaybolsa bile, Kalman Filtresi sayesinde tahmini lokasyon belirlenmiştir. Program kodlarının ince ayarı sayesinde başarılı bir takip sağlanmıştır. Program, hedefin bir parçası olarak hareket eden gölgeyi takip etmeye devam etmiştir.

Visual Target Detection and Tracking Based on Kalman Filter

In this study, in order to prevent collision and target tracking in autonomous aircraft, Kalman filter with appropriate solutions for target detection and tracking problems are presented. For the Kalman filter application, the motion- based tracking method that facilitates the tracking of multiple objects has been used. A background subtraction algorithm was used for the detection of moving objects while corrective actions were applied to the foreground mask to eliminate noise, and the connected pixel groups correspond to moving objects were identified. The used image represents an image taken by a hovering drone. Although the tracked multiple targets disappeared behind the obstacle, the estimated location was determined by means of Kalman filter. Thanks to the fine tuning of the program codes, a successful follow-up has been achieved. The program has continued to follow the moving shadow as a part of the target.

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