Moving Object Detection Based on Improved Codebook Model

DOI

10.2991/mic-15.2015.4How to use a DOI?

Keywords

-background modeling; codebook; moving object detection; noise robustness

Abstract

Background modeling is a key technology in video surveillance field. Conventional methods used to detect the moving object have drawbacks in the aspects of accuracy and robustness. In order to address these problems, we change the RGB columnar structure in traditional codebook model and establish codebook background model in the YUV color space. We cluster every pixel on a timeline in an image and extract background templates. Then the current image and the background templates are compared. At the same time, the background templates are renewed. We integrate the frequency information to improve the process of symbol decision, deletion and matching. In the meantime, the spatial information of current pixel is added into the prediction of the foreground, making the results of foreground detection more reliable. The experimental results indicate that the proposed method can detect the moving objects effectively and correctly under various conditions. In addition, the proposed algorithm also has the good noise robustness.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Gao Ruidong
PY  - 2015/08
DA  - 2015/08
TI  - Moving Object Detection Based on Improved Codebook Model
BT  - Proceedings of the 2nd International Conference on Modelling, Identification and Control
PB  - Atlantis Press
SP  - 16
EP  - 20
SN  - 1951-6851
UR  - https://doi.org/10.2991/mic-15.2015.4
DO  - 10.2991/mic-15.2015.4
ID  - Ruidong2015/08
ER  -