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http://dx.doi.org/10.5909/JEB.2011.16.1.178

Object Tracking Based on Color Centroids Shifting with Background Color and Temporal filtering  

Lee, Suk-Ho (computer and information engineering, Dongseo university)
Choi, Eun-Cheol (TMS information technology, Yonsei university)
Kang, Moon-Gi (TMS information technology, Yonsei university)
Publication Information
Journal of Broadcast Engineering / v.16, no.1, 2011 , pp. 178-181 More about this Journal
Abstract
With the development of mobile devices and intelligent surveillance system loaded with pan/tilt cameras, object tracking with non-stationary cameras has become a topic with increasing importancy. Since it is difficult to model a background image in a non-stationary camera environment, colors and texture are the most important features in the tracking algorithm. However, colors in the background similar to those in the target arise instability in the tracking. Recently, we proposed a robust color based tracking algorithm that uses an area weighted centroid shift. In this letter, we update the model such that it becomes more stable against background colors. The proposed algorithm also incorporates time filtering by adding an additional energy term to the energy functional.
Keywords
Object tracking; Centroid shifting; Background colors;
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1 Suk-Ho Lee, Euncheol Choi and Moon Gi Kang, "Object tracking based on area weighted centroids shifting with spatiality constraints", IEEE ICIP2008, San Diego, USA, Oct. 12-15, 2008   DOI
2 D. Comaniciu, v. Ramesh, and P. Meer, "Kernel-based object tracking," IEEE Trans. on PAMI, vol. 25, pp. 564-75, 2003.   DOI   ScienceOn
3 G. R. Bradski, "Computer vision face tracking for use in a perceptual user interface," Intel Technology Journal, 2nd Quarter,1998.
4 A. Yilmaz. "Object tracking by asymmetric kernel mean shift with automatic scale and orientation selection," In IEEE Conf. on Computer Vision and Pattern Recognition, 2007.   DOI
5 A. Babaeian, S. Rastegar, M. Bandarabadi, and M. Rezaei, "Mean shift-based object tracking with multiple features," Southeastern Symposium on System Theory, pp. 68 - 72, 2009
6 P. Li, "An Adaptive Binning Color Model for Mean Shift Tracking," IEEE Transactions on Circuits and Systems for Video Technology, pp. 1293 - 1299, Vol. 18, 2008   DOI   ScienceOn