Target Detection Algorithm Based on Improved Gaussian Mixture Model

DOI

10.2991/icecee-15.2015.163How to use a DOI?

Keywords

Gaussian mixture model. Improved Gaussian mixture model. moving object detection.

Abstract

With the traditional Gaussian mixture model being more sensitive to light and failing to react to changes of lighting, a variances and a mean update program under local illumination and global illumination mutations are puts forward respectively in this paper. More specifically, a divergent method to update the mean of each Gaussian distribution in the background model is proposed, following the analyses of the average grey value of current image frame and the absolute difference of the average grey value of the background model. An innovative update method to update the variance of Gaussian mixture model is also presented, based on the study of the absolute value of the pixel value and mean value. Experimental results show that the algorithm can not only detect moving targets in a relatively more complete manner, but also exhibits better adaptability and robustness for outdoor lighting mutation.

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  - Xiaomeng Wang
AU  - Dequn Zhao
AU  - Guangmin Sun
AU  - Xingwang Liu
AU  - Yanli Wu
PY  - 2015/06
DA  - 2015/06
TI  - Target Detection Algorithm Based on Improved Gaussian Mixture Model
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 846
EP  - 850
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.163
DO  - 10.2991/icecee-15.2015.163
ID  - Wang2015/06
ER  -