DocumentCode
1887849
Title
Notice of Retraction
A Method for Obtaining Regions of Interest with Adaptive Gaussian Mixture Model
Author
Qing Lin ; Jia Li ; Zhenjie Shi ; Yongzhao Zhan
Author_Institution
Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China
fYear
2010
fDate
25-26 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper an adaptive Gaussian mixture model is introduced firstly to remove the shadow of regions of interest in the detection of moving human body from current video sequences. Then use a proposed method of obtaining ROI. From the view of the tracking effect, it can be concluded that this method of removal shadow of regions of interest can improve the precision rate of segment of moving people and is good for subsequent tracking. The experimental result showed the ROI produced by this method and is robust, and is suitable for real- time tracking.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper an adaptive Gaussian mixture model is introduced firstly to remove the shadow of regions of interest in the detection of moving human body from current video sequences. Then use a proposed method of obtaining ROI. From the view of the tracking effect, it can be concluded that this method of removal shadow of regions of interest can improve the precision rate of segment of moving people and is good for subsequent tracking. The experimental result showed the ROI produced by this method and is robust, and is suitable for real- time tracking.
Keywords
Gaussian processes; image motion analysis; image sequences; object tracking; video signal processing; adaptive Gaussian mixture model; human body moving detection; moving people; real time tracking; regions of interest; tracking effect; video sequence; Adaptation model; Computational modeling; Image color analysis; Pixel; Target tracking; Video sequences; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location
Wuhan
ISSN
2156-7379
Print_ISBN
978-1-4244-7939-9
Type
conf
DOI
10.1109/ICIECS.2010.5677778
Filename
5677778
Link To Document