Motion Detection with Background Modelling and Optical Flow

Year 2021, Volume: 14 Issue: 3, 223 - 228, 31.07.2021

İbrahim Delibaşoğlu

https://doi.org/10.17671/gazibtd.846961

Abstract

Motion detection is a challenging task and may be used as a pre-processing step in different computer vision tasks. Methods proposed for motion detection are mostly based on background modelling and subtraction. In this study, a method is proposed with background modelling and optical flow vectors. Farneback method is applied to estimate optical flow vectors. Optical flow is used to determine the threshold value of each pixel applied in background subtraction step of proposed method. The experimental results show that proposed approach using optical flow in background subtraction improves the performance according to a static threshold. The proposed method is evaluated on different subset images of CDNET-2014 dataset and has a reasonable performance against methods in the literature. Proposed method has similar performance in the F1 metric compared to the methods in the literature, but it is observed that it has the best average performance in the PWC metric, which gives the ratio of wrongly detected or missed moving pixels.

Keywords

motion detection, moving object detection, optical flow

Arkaplan Modellemesi ve Optik Akış ile Hareket Tespiti

Abstract

Hareket tespiti çeşitli bilgisayarlı görme problemlerinde ön-işlem aşamasında kullanılmaktadır ve üzerinde çalışılan önemli konulardan birisidir. Hareket tanıma için önerilen yöntemler çoğunlukla arka plan modellemesi ve çıkarımına dayanmaktadır. Bu çalışmada, arka plan modelleme ve optik akış vektörlerinin kullanıldığı bir yöntem önerilmiştir. Optik akış tahmin edilmesinde Farneback yöntemi kullanılmıştır. Önerilen yöntemde optik akış, arka plan çıkarımı aşamasında her bir piksel için uygulanacak eşik değeri belirlemek için kullanılmıştır. Deneysel sonuçlar arka plan çıkarımı yaparken optik akış bilgisini kullanmanın sabit eşik değer uygulamaya nazaran performansı arttırdığını göstermiştir. Önerilen yöntem CDNET-2014 veri kümesinden farklı altküme görüntüleri üzerinde değerlendirilmiş ve literatürdeki yöntemler karşısında iyi sonuçlar elde edilmiştir. F1 performans kriterinde literatürdeki yöntemlere çok yakın sonuçlar elde edilirken, hatalı tespit edilen veya ıskalanan hareketli piksel oranını veren PWC metriğinde ise en iyi ortalama performansa ulaşıldığı gözlemlenmiştir.

Keywords

hareket tespiti, hareketli nesne tespiti, optik akış

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