Target Detection Algorithm Based on Improved Gaussian Mixture Model
Xiaomeng Wang, Dequn Zhao, Guangmin Sun, Xingwang Liu, Yanli Wu
Available Online June 2015.
- https://doi.org/10.2991/icecee-15.2015.163How to use a DOI?
- Gaussian mixture model. Improved Gaussian mixture model. moving object detection.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2015 2nd 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 - https://doi.org/10.2991/icecee-15.2015.163 ID - Wang2015/06 ER -