Nesne tespit ve takip metotları: Kapsamlı bir derleme

Görüntü işleme dijital bir görüntü içerisindeki önemli bilgilerin okunması, çıkartılması ve işlenmesi için kullanılan bir yöntemdir. Görüntü içerisinde bulunan bir nesne ya da bir ortam hakkında insan görme sistemine benzer şekilde nitel bilgiler edinilmesi ve kullanılması görüntü işlemenin temel amaçlarındandır. Görüntülerde bulunan nesnelerin tespiti, tanımlanması, sınıflandırılması ve takibi gibi ihtiyaçları karşılayacak birçok yöntem geliştirilmiştir. Özellikle görüntülerdeki hedef nesnenin bulunması ve ileriki zaman dilimlerinde bu nesnenin kaybedilmemesi birçok alandaki uygulamalarda sıklıkla kullanılmaktadır. Takip edilecek nesnenin değişken bir ortam içinde bulunması nesne takibi ve analizini zorlaştıran temel problemdir. Bu problemleri çözmek ve nesnenin başarılı bir şekilde takip edilmesi için birçok farklı yöntem gelişmiştir. Bu çalışmada nesne takibi için güncel ve yaygın kullanılan yöntemler ele alınmıştır. İncelenen yöntemler güçlü/zayıf yönleri ile irdelenmiştir.

Anahtar Kelimeler:

Nesne izleme, arka plan çıkarma, nesne algılama, performans analizi, nesne sınıflandırması

Object detection and tracking methods: A comprehensive review

Image processing is a method for reading, extracting, and processing important data in a digital image. One of the fundamental part of the image processing is collecting knowledge acquisition about recognized objects and environments in the image like human vision system. Many methods are developed to meet the needs of detection, identification, classification and tracking of objects in images. Especially, finding the target object in the images and following this object in the future time periods is frequently used in many applications. One of the main problems which makes object tracking and analysis difficult is tracking the object in a changing environments. Several effective methods are developed in order to solve these kinds of problems. In this paper, current and widely used methods for object tracking are discussed and those methods were examined with their strengths and weaknesses.

Keywords:

Object tracking, background subtraction, object detection, performance analysis, object classification,

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