Moving Object Detection and Localization in Camera-Trap Images

Year 2019, Volume: 12 Issue: 2, 902 - 919, 31.08.2019

Emrah Şimşek , Özyer Barış Gülşah Tümüklü Özyer

https://doi.org/10.18185/erzifbed.509571

Cited By: 1

Abstract

Camera-traps are usually placed on a fixed point in a forest land and are used to monitor natural life. Millions of images are recorded to investigate the natural life of living things by using camera-traps. Computer based automatic methods are developed for detecting and identifying living things on recorded images. Also problems such as background complexity, moving background, change of light intensity and fragmentations of the object in camera-trap images make moving object detection difficult. In the literature, for this purpose the model images of moving objects obtained from manually are used as preliminary information in classification based methods. Detecting and cropping model images of the objects manually is a difficult, laborious, time-consuming process and requires high workload. In our study, To reduce this workload it was aimed to detect moving objects automatically and to determine the location of moving objects in camera-trap images that obtained from natural environment. In the proposed method for this purpose, background extraction and frame difference methods were applied to the images. Gaussian Average and Mixture of Gaussian were used to create a background model. Gaussian Blur and Median Filter were used to reduce noise and to clarify objects. .OTSU thresholding was used to eliminate the errors of foregrounds. In the camera-trap data sets, the success of detecting moving objects was 82% and the object localization success was 80%.

Foto-kapan Görüntülerinde Hareketli Nesne Tespiti ve Konumunun Belirlenmesi

Abstract

Foto-kapanlar
genellikle ormanlık arazide sabit noktaya yerleştirilmiş ve doğal yaşamı
izlemek için kullanılan görüntüleme cihazlarıdır. Foto-kapanlar kullanılarak
canlıların doğal yaşamı üzerinde araştırma yapmak amacıyla milyonlarca görüntü
kaydedilmektedir. Kaydedilmiş görüntüler üzerinde bilgisayar tabanlı yöntemler
ile canlıların tespit edilmesi ve tanınması amacıyla otomatik yöntemler
geliştirilmektedir. Ayrıca foto-kapan görüntülerinde arka plan
karmaşıklığı, arka planın hareketli olması, ışık şiddeti değişimi ve nesnenin
parçalı olması gibi problemler hareketli nesne tespitini zorlaştırmaktadır.
Literatürde bu amaçla yapılan çalışmalarda hareketli nesnelere ait model
görüntüler görüntü içerisinden el ile tespit edilerek sınıflandırma tabanlı
yöntemlerde ön bilgi olarak kullanılmaktadır. Nesnelere ait model
görüntülerin el ile tespit edilmesi ve kırpılması zor, zahmetli, zaman alan bir
süreçtir ve yüksek iş yükü gerektirmektedir. Çalışmamızda bu iş yükünü azaltmak
amacıyla doğal ortamdan elde edilmiş foto-kapan görüntülerinde nesnelere ait ön
bilgi kullanılmadan hareketli nesneler otomatik tespit edilmiş ve hareketli
nesnelerin görüntüdeki konumları belirlenmiştir. Önerilen yöntemde hareketli
nesnelerin tespit edilmesi için görüntülere arka plan çıkarma ve çerçeve farkı
yöntemleri uygulanmıştır. Arka plan modelinin oluşturulması için Değişen Gauss
Ortalama ve Gaussların Karışımı, gürültülerin azaltılması ve nesnelerin
belirginleştirilmesi amacıyla Gauss Bulanıklığı ve Medyan filtre, ön plan
tespitindeki hataların giderilmesi için OTSU eşikleme kullanılmıştır.
Foto-kapan veri setlerinde hareketli nesne tespit etme başarısı %83, nesne
konumlandırma başarısı ise %80 olarak elde edilmiştir.

Keywords

Hareketli Nesne Tespiti, Değişen Gauss Ortalama, Çerçeve Farkı, Fotokapan

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