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
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;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.340