Title : ( A Background Model Initialization Algorithm Based on QR-Decomposition )
Authors: Mahmood Fathy , Morteza Analoui , Nasser Mozayani , Mahmood Amintoosi , Farzam Farbiz ,Abstract
Background subtraction is a major part of many motion detection, tracking and surveillance systems. In this paper a new algorithm for the purpose of the background model initialization has been presented. The key idea of the proposed method lies in the identification of the background based on QRDecomposition method in linear algebra. R-values produced with QR-Decomposition can be applied to decompose a given system to indicate the degree of the significance of the decomposed parts. We split the image into small blocks and select the background blocks with the weakest contribution, according to the assigned R-values. The main advantage of the proposed method is that in contrast to many other methods, here, there is no need for an empty scene with no foreground object. Simulation results showed that the proposed method produced better background model with respect to some others.
Keywords
, Background Subtraction, QRDecomposition, Gaussain Mixture Model, Singular Value Decomposition@inproceedings{paperid:1106569,
author = {محمود فتحی and مرتضی آنالوئی and ناصر مزینی and Amintoosi, Mahmood and فرزام فربیز},
title = {A Background Model Initialization Algorithm Based on QR-Decomposition},
booktitle = {4th Iranian Conference on Machine Vision and Image Processing},
year = {2007},
location = {مشهد, IRAN},
keywords = {Background Subtraction; QRDecomposition; Gaussain Mixture Model; Singular Value Decomposition},
}
%0 Conference Proceedings
%T A Background Model Initialization Algorithm Based on QR-Decomposition
%A محمود فتحی
%A مرتضی آنالوئی
%A ناصر مزینی
%A Amintoosi, Mahmood
%A فرزام فربیز
%J 4th Iranian Conference on Machine Vision and Image Processing
%D 2007
