DocumentCode
479957
Title
An Algorithm of Mean-Shift Template Update Based On Mixture Gaussian Model
Author
Sixing, XIAO ; Jingxin, Hong ; Xiaozhu, Xie
Author_Institution
Comput. Dept., Xiamen Univ., Xiamen
Volume
2
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
1040
Lastpage
1044
Abstract
To improve the limitation of Mean-Shift lack of the template update, an algorithm based on mixture Gaussian model is proposed. It treats the target region as ldquobackgroundrdquo, and three Gaussian functions are used to evaluate each pixel value in the target region. After using Mean-Shift algorithm to track the target region in the current frame, we update the Mixture Gaussian Model with the new target region in the current frame, so that the current target template can update automatically with the changing surveillance of selected target. Experiment results show that this algorithm can successful track the changing target surveillance under the condition of change illumination and surface.
Keywords
Gaussian processes; object detection; surveillance; target tracking; mean-shift template update; mixture Gaussian model; surveillance; target tracking; Color; Computer science; Computer vision; Histograms; Kernel; Software algorithms; Software engineering; Surveillance; Target tracking; Taylor series; Mean-Shift Algorithm; Mixture Gaussian Model; object tracking; template update;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.340
Filename
4722229
Link To Document