International Journal of Computer Theory and Engineering

Editor-In-Chief: Prof. Mehmet Sahinoglu
Frequency: Quarterly
ISSN: 1793-8201 (Print), 2972-4511 (Online)
Publisher:IACSIT Press

OPEN ACCESS
4.0
CiteScore

IJIET 2010 Vol.2(2): 274-282
doi: 10.7763/IJCTE.2010.V2.152

A Novel Approach in Video Scene Background Estimation

Hamidreza Baradaran Kashani1 , Seyed Alireza Seyedin1 , Hadi Sadoghi Yazdi2

  • 1Electrical Department, Ferdowsi University of Mashhad, Iran. Postal Code: 9177948944, P.O. Box:1111
  • 2Computer Department, Ferdowsi University of Mashhad, Iran. Postal Code: 9177948944, P.O. Box:1111

Abstract

This paper presents a novel method for background estimation in a video sequence from the function estimation point of view. The proposed algorithm, called Kernel-based Background Learning (KBL), is designed based on kernel machine joint with learning schemes. In order to estimate background using KBL algorithm, we first interpret foreground samples as outliers relative to the background ones and so propose an Outlier Separator (OS). Then, the obtained results of OS algorithm are employed in the KBL method in order to train and estimate background in each pixel. Experimental results show the high accuracy and effectiveness of the proposed method in background estimation and foreground detection for the scenes including moving backgrounds, camera shakes, and non-empty backgrounds.

Keywords

  • Background estimation
  • outlier separator
  • kernel-based background learning
152-G643

How to Cite

Copied

Hamidreza Baradaran Kashani, Seyed Alireza Seyedin, and Hadi Sadoghi Yazdi, "A Novel Approach in Video Scene Background Estimation," International Journal of Computer Theory and Engineering, vol. 2, no. 2, pp. 274-282, 2010. https://doi.org/10.7763/IJCTE.2010.V2.152

Copyright & License

Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Article Metrics in Dimensions

Menu