Centre of mass model - A novel approach to background modelling for segmentation of moving objects
Yükleniyor...
Dosyalar
Tarih
2007
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper describes a novel method, centre of mass model, to detect moving objects in a dynamic scene based on background subtraction. Any displacement of the position of centre of mass (CoMs) in two consecutive frames is the indicator of a moving object in a scene. Dividing a scene into subregions and modelling them as individual masses allow segmentation of the moving object(s). In the proposed scheme, an image is divided into blocks that are called super-pixels and each super-pixel is represented with the x and y components of CoM of a block. The segmentation is achieved by taking the absolute difference between CoM of current super-pixel and the mean of CoMs of previous corresponding super-pixels, and thresholding the difference with a dynamically updated value. A comparative work has been carried out to evaluate the performance of the proposed model and the previously reported seven different methods. The model produced consistent outputs for the images taken in different environmental conditions. The moving objects were successfully segmented with no post-processing operations. Centre of mass model demonstrated better overall performance than the methods previously reported. Its output was superior for auto-focused video images. (c) 2007 Published by Elsevier B.V.
Açıklama
Anahtar Kelimeler
centre of mass, image modelling, motion segmentation, background subtracting
Kaynak
Image and Vision Computing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
25
Sayı
8
